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M8581 |
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Faculty
Objectives
1- Interpret the importance and usefulness of financial statements for the various stakeholders;
2 - Recognize the impact of the main transactions on the different cycles of operations.
3 - Differentiate the main corporate governance models and the importance of internal and external control mechanisms.
Program
1. The Accounting Standardization System
- Framework;
- Qualitative characteristics of the information;
- Purpose and structure of the financial statements;
- Other fundamental concepts.
2. The impact of transactions on cycles of operations
- Operational cycle;
- Investment cycle;
- financing cycle.
3. Corporate Governance and Control
- Corporate governance models;
- Internal control;
- Legal certification of accounts;
- Integrated accounting reporting.
Evaluation process
The process of assessment in this curricular unit covers the following methods:
1) Assessment throughout the semester;
2) Assessment by exam.
The assessment method mentioned in 1) includes a Mid-term test (with a weighting of 40% in the final grade) and a Final Teste (with a 60% weighting in the final grade). The minimum mark in each of the mentioned tests is 7.5 points (in a 20 points scale).
In case of "Assessment by exam", it occurs excusively during the assessment period and covers all the material taught in the curricular unit, with a weighting of 100% in the final grade.
Bibliography
Mandatory Bibliography
Title: Horngreen, C; Sundem, Gary L.; Elliott,John A.; Philbrick, Donna (2023). Introduction to Financial Accounting, 11th Edition, New Jersey: Pearson.
Lopes, I. T. (2022). Contabilidade e Finanças para Gestores Não Financeiros, 2ª Edição, Coimbra: Edições Almedina.
Comissão de Normalização Contabilística, SNC - Sistema de Normalização Contabilística (Decreto-Lei n.º158/2009, de 13 de julho.
Authors:
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Optional Bibliography
Title: Lopes, I. T. (2022). Contabilidade Financeira: Teoria e Prática, Coimbra: Editora d' Ideias;
Código das Sociedades Comerciais.
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04290 |
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Faculty
Objectives
This course aims to enhance students' understanding of distributed database management systems (DBMS). It focuses on providing practical skills in designing, implementing and managing these databases, considering challenges such as replication and fragmentation. The curricular unit highlights the importance of guaranteeing the consistency and durability of data in distributed environments, as well as the efficient integration of multiple databases. Finally, it seeks to encourage students to have a critical and analytical view of future trends and innovations in this field.
Program
1. Introduction to Distributed Database Management Systems (DBMS)
2. Distributed Database Project
3. Distributed Data Control
4. Distributed Transaction Processing
5. Data Replication
6. Database Integration
Evaluation process
Given its eminently practical nature, the UC does not provide an assessment by exam.
Therefore, the evaluation will take place in the following ways:
1st season:
1. [60%] Group work with individual presentation and discussion* (min. 10 points)
2. [40%] Written test (min. 8 marks)
* individual discussion is decisive, as poor performance may result in failure in the UC, regardless of the quality of the group work delivered.
2nd season and Special Season:
3. [60%] Individual work without presentation or discussion (min. 10 points)
4. [40%] Written test (min. 8 points)
Bibliography
Mandatory Bibliography
Title: • M. Tamer Ozsu and Patrick Valduriez. (2019). Principles of Distributed Database Systems (4th. ed.). Springer Publishing Company, Incorporated.
• White, Tom. (2015). Hadoop: The Definitive Guide (4th. ed.). O'Reilly Media, Inc. ISBN: 9781491901632
Authors:
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Optional Bibliography
Title: • Moniruzzaman, A B M & Hossain, Syed. (2013). NoSQL Database: New Era of Databases for Big data Analytics - Classification, Characteristics and Comparison. Int J Database Theor Appl. 6.
• Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber. (2006). Bigtable: a distributed storage system for structured data. In Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7 (OSDI '06). USENIX Association, USA, 15.
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M8406 |
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Faculty
Objectives
LO1- Identify and apply digital communication techniques to real mobile communication systems
LO2- Identify, compare and evaluate the dimensioning, planning and radio resource management of 4G
LO3- Identify, compare and evaluate the dimensioning, planning and radio resource management of 5G and B5G
Program
PC.1 Study of digital communication techniques for mobile networks
PC.2 Study of LTE. Radio network planning of 4G
PC.3 Study of LTE-Advanced and LTE-Pro
PC.4 Study of 5G Use Cases and Applications
PC.5 Study of 5G New Radio. Key Technologies, Numerologies. Frequency Bands and Waveforms
PC.6 Study of 5G Core Network, Evaluation of Cost in 5G networks
PC.7 Study of Dimensioning and Planning of 5GNR Radio networks
PC.8 Study of 5GNR Private Radio Networks
PC.9 Study of Non-Terrestrial Networks of Beyond 5G (B5G)
Evaluation process
Evaluation throughout the semester: Attendance at least 50% of classes. In this modality, the evaluation is done in three parts. Active participation in a class 5%. The second part consists of a group work on 5G/5GNR simulation scenarios with individual evaluation at the end of classes and the third part consists of a test. The grade of the group work with individual evaluation has a weight of 30%. The remaining 65% is obtained with the grade of the test. Minimum grade of 7.5 in the test.
Evaluation by exam: In this modality, the evaluation is made by the 1st exam (equals to Final written test) or 2nd exam with a minimum grade of 9.5 and a weight of 100% in the final grade.
If the student has taken both types of assessment, the final grade of the subject will be the better of the two.
There is a Special Exam in July (it requires authorization and registration) for the students that have not been successful, previously.
Bibliography
Mandatory Bibliography
Title: [1] H. Holma, A. Toskala, "WCDMA for UMTS", John Wiley, 2005
[2] H. Holma, A. Toskala, "LTE for UMTS - OFDMA and SC-FDMA based radio access", John Wiley, 2009
[3] C. Cox, ?An Introduction to LTE", John Wiley, 2012
[4] W. Xiang, K. Zheng, X. Shen, "5G Mobile Communications", Springer Publishing, 2017
[5] A. Osseiran, J. Monserrat, P. Marsch, "5G Mobile and Wireless Communications Technology", Cambridge University Press, 2016
[6] L. Miller, J. Cavazos, "5G & Beyond", Keysight Technologies, John Wiley, 2022
Authors:
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Optional Bibliography
Title: [7] 3GPP specifications about LTE and 5G Novel Radio
[8] Transmission Techniques for 4G Systems, M. Silva, A. Correia, R. Dinis, N. Souto, J. C. S. Silva, CRC-Taylor & Francis Group, FL, USA, 2013.
[9] Transmission Techniques for Emergent Multicast and Broadcast Systems, M. Silva, A. Correia, R. Dinis, N. Souto, J. C. Silva, CRC-Taylor & Francis Group, FL, USA, 2010.
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04291 |
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Faculty
Objectives
After successfully attending the curricular unit, students should be able to:
OA1. Know the fundamental concepts of network science
OA2. Know the essential metrics and methods for describing and analyzing networks
OA3. Know how to use network analysis and visualization software
OA4. Know how to collect data, analyze and model networks
OA5. Know how to analyze diffusion processes in networks
OA6. Implement a network analysis solution to solve a given problem.
Program
CP1. Introduction to the notion of network and Network Science
CP2. Software for network analysis
CP3. Graphs and network metrics
CP4. Static network models
CP5. Power laws and scale-free networks
CP6. Dynamic network models
CP7. Strategic network models
CP8. Processes in networks, percolation, diffusion and research
CP9. Robustness and resilience
CP10. Communities
CP11. Higher order networks and temporal networks
Evaluation process
Given the practical nature of the contents, the assessment will encompass a project. Its subject should be aligned with all or part of the syllabus.
Exercises in class (10%).
Project (90%), including teamwork (report and software: 40%, and oral exam: 50%).
All components of the project - proposal, report, software, and oral exam, are mandatory. The minimal classification for each component is 10 on a scale of 0 to 20.
There will be a unique deadline for submitting the project, except for students accepted to the special period of assessment, that will be allowed to submit during that period.
Presence in class is not mandatory.
There is no final exam.
Students aiming to improve their classification can submit a new project in the following scholar year.
Bibliography
Mandatory Bibliography
Title: Mark Newman , ?Networks?, second edition, Ed. Oxford University Press, 2020
Albert-Laszlo Barabasi, ?Network Science?, Ed. Cambridge University Press, 2016
Available online at http://networksciencebook.com
Authors:
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Optional Bibliography
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M4310 |
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Faculty
Objectives
After completing this course unit the student should be able to:
LO1. Know the fundamentals of functional programming
LO2. Apply meta-programming mechanisms
LO3. Design APIs (application programming interfaces)
LO4. Develop reusable software
Program
PC1. Introduction to Kotlin programming language
PC2. Meta-programming and annotations
PC3. Design patterns for extensibility
PC4. Plugin-based systems
Evaluation process
Periodic assessment:
- In-class quizzes (20%)
- Mid-term project evaluation (20%), to present during the semester
- Project (60%), to deliver and defend during the exam season
It is compulsory to attend at least 50% of the scheduled lectures and lab classes.
Project is the only form of evaluation, it is not possible to be evaluated through an exam. Evaluation in Época Especial requires delivering and defending the Project, with the requirement that its development should have been supervised during the semester classes.
Bibliography
Mandatory Bibliography
Title: André L. Santos, Livro digital de apoio (Kotlin, padrões de desenho), 2021.
Authors:
Reference:
Year:
Optional Bibliography
Title: Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides. Design Patterns. Elements of Reusable Object-Oriented Software, Addison-Wesley, 1995.
Joshua Bloch, Effective Java (3ª edição), 2017.
Dmitry Jemerov and Svetlana Isakova, Kotlin in Action, Manning, 2017.
David Farley, Modern Software Engineering: Doing What Works to Build Better Software Faster, Addison-Wesley, 2021.
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03332 |
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Faculty
Objectives
A. Knowledge and Understanding:
- Understanding the main concepts involved in the debate on the African diasporas.
- Knowledge of the historical events that marked the social and political trajectory of the African diasporas.
- Knowledge of the most relevant debates in the field of strategies and policies for collective action of diasporas.
B. Application of knowledge:
- Ability to use the knowledge gained to derive implications on different diaspora experiences at the transnational level.
- Ability to use the knowledge acquired to discuss and critically evaluate contemporary challenges of diasporas.
C. Communication:
- Ability to elaborate theoretically, logically and factually reasoned arguments and to communicate them to others.
D. Learning:
- Capacity for study and personal research with autonomy;
- Ability and motivation for life long learning
Program
1.Historical and theoretical issues of the African diasporas
1.1.From the enslaved people trafficking to the current migrations
1.2.Presence and forms of collective African action in Portugal and Europe (XV-XVIII)
1.3.Integration of immigrants and migration politics
2.Political and social issues of the African diasporas
2.1.Forms of resistance to slavery in the American continent
2.2.Diasporas and Anti-Colonial Movements: Pan-Africanism and Civil Rights Movements
2.3.From the Nativists of the 1st Republic to the Casa dos Estudantes do Império and Liberation Struggles in Portugal and Africa
3.Political and social issues of the African diasporas in the present
3.1.Racism and the African Diaspora in post-colonial Europe
3.2.Forms of collective action of diaspora in contemporary times
3.3.Intersectionality, Black Feminist and LGBTI Movements
3.4.African and Black Resistance in Democratic Portugal:From African Immigrants Associations to the Portuguese Black and Afrodescendant Movement
Evaluation process
1. Continuous assessment
- Group presentation in class (40%)
- Essay writing on a program theme (45%)
- Active participation in classes (15%)
2. Final exam
Bibliography
Mandatory Bibliography
Title: TINHORÃO, José Ramos (1997), Os Negros em Portugal: Uma Presença Silenciosa, Lisboa: Caminho
SANCHES, Manuela Ribeiro (2011), Malhas que os Impérios Tecem: Textos Anticoloniais, Contextos Pós-Coloniais, Lisboa: Edições 70
PIRES, Rui Pena (2003), Migrações e Integração, Oeiras: Celta Editora
MACHADO, Fernando Luís (2009), ?Quarenta anos de imigração africana: um balanço?, Ler História, 56, pp. 135-165
JAMES, C.L.R. (1963 [1938]), The Black Jacobins: Toussaint L'ouverture and the San Domingo Revolution, New York: Vintage Books
HALL, Stuart (2003), Da Diáspora: Identidades e Mediações Culturais, Belo Horizonte: UFMG/UNESCO
GILROY, Paul (2012), O Atlântico Negro: Modernidade e Dupla Consciência, Rio de Janeiro: Centro de Estudos Afro-Asiáticos/Editora 34
DUBOIS, W.E.B. (1992 [1935]), Black Reconstruction in America, 1860-1880, New York: Free Press
DAVIS, Angela (2016 [1981]), Mulheres, Raça e Classe, São Paulo:Boitempo
Authors:
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Year:
Optional Bibliography
Title: AFROLIS - Audioblogue Rádio AfroLis. https://radioafrolis.com/
ALMEIDA, Sílvio (2019), Racismo Estrutural, São Paulo: Feminismos Plurais.
BORGES, Sónia Vaz (2014), Na Pó di Spéra: percursos nos bairros da Estrada Militar, de Santa Filomena e da Encosta Nascente, Cascais: FCG/Principia.
CABRAL, Amilcar (1974), Textos Políticos, Porto: Gráfica Firmeza.
CARMICHAEL, Stokely, Charles V. Hamilton (1961), Black Power: The Politics of Liberation, New York: Vintage. 9.
CARTA ABERTA DE ORGANIZAÇÕES AFRODESCENDENTES PORTUGUESAS AO CERD -2016. https://museudigitalafroportugues.wordpress.com/2016/12/08/carta-aberta-de-organizacoes-afrodescendentes-portuguesas-ao-cerd-2016/
DAVIS, Angela (2016 [1981]), Mulheres, Raça e Classe, São Paulo: Boitempo.
FANON, Frantz (1975 [1952]), Peles Negras, Máscaras Brancas, Porto: Paisagem Editora.
FANON, Frantz (2015 [1961]), Os Condenados da Terra, Lisboa: Letra Livre.
HENRIQUES, Joana Gorjão (2016), Racismo em Português, Lisboa: Tinta da China.
HALL, Stuart (2003), Da Diáspora: Identidades e Mediações Culturais, Belo Horizonte: UFMG/UNESCO
MACHADO, Fernando Luís (2009), Quarenta anos de imigração africana: um balanço?, Ler História, 56, pp. 135-165.
MATA, Inocência (2015), A Casa dos Estudantes do Império e o lugar da literatura na consciencialização política, Lisboa: UCCLA.
PIRES, Rui Pena (2003), Migrações e Integração, Oeiras: Celta Editora.
PLATAFORMA GUETO Resposta à Alta Comissária (A.C.I.DI). https://plataformagueto.wordpress.com/noticias/resposta-a-alta-comissaria-a-c-i-di/ 29.
SOS RACISMO (2016), Racismo e Discriminação ? A lei da impunidade, Lisboa: SOS´
SANCHES, Manuela Ribeiro (2011), Malhas que os Impérios Tecem: Textos Anticoloniais, Contextos Pós-Coloniais, Lisboa: Edições 70.
TAYLOR, Keeanga-Yamahtta (2016), From #BlackLivesMatter to Black Liberation, Chicago: Haymarket Books.
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00023 |
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Faculty
Objectives
The course aims to introduce the students to a detailed knowledge of African realities in the social and cultural domains.mIn this way, the learning objectives of the course are
1. To know the construction of central concepts, relevant to analyse the African social and cultural fields.
2. To understand the discursive constructions of the African continent.
3. To acquire a critical view on themes of social and cultural dynamics in Africa.
4. To identify the main identity constructions in Africa.
5. To know social and cultural movements in Africa and their impacts.
Program
1. Representations of Africa and post-colonialism
1.1. Coloniality, discourse and Eurocentrism
1.2. The symbolic construction of the African continent
2. Selected themes of social and cultural dynamics in Africa
2.1. Ethnicity and culture
2.2. Indigenous peoples and the production of knowledge
2.3. Social movements and political and social change
2.4. Religion and religious syncretism
2.5. Feminisms in Africa
2.6. Cultural movements and youth in Africa
2.7. Popular culture, music and cinema
Evaluation process
1. Assessment throughout the semester
The assessment consists of the weighted average of:
a) Attendance to and active participation in the classes (minimum of 70%)- 30%
b) Essay (5000-5500 words): 70%
The essays can be submitted in Portuguese, English, French or Spanish and delivered in dates agreed at the Council of the Year meeting (first, second and special). The essays don't count for students who will do a final exam.
2. Final exam for students who are not in continuous assessment.
Bibliography
Mandatory Bibliography
Title: Obadare, Ebenezer (Ed), 2014, The Handbook of Civil Society in Africa, New York: Springer
Mudimbe, Valentin Y., 1988, The Invention of Africa: Gnosis, Philosophy and the Order of Knowledge, Bloomington: Indiana University Press
Mkandawire, Thandika (ed.), 2005, African Intellectuals: Rethinking Politics, Language, Gender and Development, Dakar: Codesria
Filho, Silvio de Almeida Carvalho e Nascimento, Washington Santos (Orgs.), 2018, Intelectuais das Áfricas, Campinas: Pontes Editores
Fanon, Frantz, 2005, The Wretched of the Earth, Grove Press
Cooper, Fred, 2002, Africa since 1940: The Past of the Present, Cambridge: Cambridge University Press
Arnfred, Signe (ed.), 2004, Re-Thinking Sexualities in Africa, Uppsala: Nordiska Afrikainstitutet
Appiah, Kwame Anthony, 1992, In My Father's House: Africa in the Philosophy of Culture, New York: Oxford University Press
Authors:
Reference:
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Optional Bibliography
Title: Clark, Msia Kibona., 2012, "Hip Hop as Social Commentary in Accra and Dar Es Salaam", African Studies Quarterly: The Online Journal of African Studies, 13(3): 23-46.
Lobato, Ramon, 2010, "Creative industries and informal economies, Lessons from Nollywood", International Journal of Cultural Studies, 13(4): 337-354
César, Amaranta, 2013, "Cinema africano, utopia e política: a tomada de palavra em Bamako, de Abderrahmane Sissako", Contemporânea, Comunicação e Cultura, 11(3): 581-590
2.8. Cultura popular, música e cinema
African Dynamics in a Multipolar World
Honwana, Alcinda, 2013, "Youth, waithood, and protest movements in Africa", Lugard Lecture 2013, ECAS 2013, 5th European Conference on African Studies,
Diouf, Mamadou, 2003, "Engaging postcolonial cultures: African youth and public space", African Studies Review, 46 (2): 1-12
Chielozona Eze, 2014, "Rethinking African culture and identity: the Afropolitan model," Journal of African Cultural Studies, 26 (2): 234-247
2.6.
AAVV, 2013, Africana, Aportaciones para la descolonización del feminismo, Barcelona: oozebap
2.5.
Reddy, Vasu, 2001, "Homophobia, human rights and gay and lesbian equality in Africa", Agenda: Empowering Women for Gender Equity, 50: 83-87
Adésínà, 'Jìmí O., 2010, "Re-appropriating matrifocality: endogeneity and African gender scholarship", African Sociological Review, 14 (1): 2-19
Aboim, Sofia, 2008, "Masculinidades na encruzilhada: hegemonia, dominação e hibridismo em Maputo", 43 (2): 273-295
2.4. Género e sexualidades
Thigo, Philip, 2013, "People, technology and spaces: towards a new generation of social movements", Journal of Contemporary African Studies, 31 (2): 255-264
Mamdani, Mahmood Thandika Mkandawire & Wamba-dia-Wamba, 1988, "Social Movements, Social Transformation and Struggle for Democracy in Africa", Economic and Political Weekly, 23(19): 973-981
de Waal, Alex and Ibreck, Rachel, 2013, "Hybrid social movements in Africa", Journal of Contemporary African Studies, 31 (2): 303-324
2.3.
Mouiche, Ibrahim, 2011, "Democratisation and Political Participation of Mbororo in Western Cameroon", Africa Spectrum, 46 (2):71-97
Anyidoho, Nana Akua, 2008, "Identity and Knowledge Production in the Fourth Generation", Africa Development, 23(1): 25-39
2.2.
Njoh, Ambe J., 2017, "The Right-To-The-City Question" and Indigenous Urban Populations in Capital Cities in Cameroon", Journal of Asian and African Studies, 52(2): 188-200
Martins, Vasco, 2015, "Ovimbundu identity attributions in post-war Angola", Journal of Southern African Studies, 41 (4): 853-867
Babou, Cheikh Anta, 2007, "Urbanizing mystical Islam: Making Murid space in the cities of Senegal", The International Journal of African Historical Studies, 40 (2): 197-223
2.1.
2.
Zeleza, Paul Tiyambe, 2006, "The Inventions of African Identities and Languages: The Discursive and Developmental Implications", in Olaoba F. Arasanyin e Michael A. Pemberton (eds), Selected Proceedings of the 36th Annual Conference on African Linguistics, Somerville: Cascadilla Proceedings Project: 14-26
Maldonado-Torres, Nelson, 2006, "Pensamento crítico desde a subalternidade: os estudos étnicos como ciências descoloniais ou para a transformação das Humanidades e das Ciências Sociais no século XXI", Afro-Ásia, 34: 105-129
Lopes, Carlos, 2012, "O legado de Amílcar Cabral face aos desafios da ética contemporânea", Via Atlântica, 21: 27-44
Césaire, Aimé, 1978, Discurso sobre o Colonialismo, Lisboa: Sá da Costa (Prefácio de Mário de Andrade)
African Studies Association, 2018, "Decolonizing African Studies", African Studies Review, 61 (3): 1-7
1.2.
1.1.
1.
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03913 |
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Faculty
Objectives
LG1. Understand why agile methodologies are important for project management specially for ITSM
LG2. Understand why ITSM is important and how complex is to apply it.
LG3. Learn about the main standards and frameworks of ITSM. The main focus should rely on ITIL.
LG4. Understand how DEVOPS works as well as how it links with ITIL and ITSM.
LG5. Learn about SCRUM methodology. Which are the main advantages and how one can apply it in practice to better manage ITSM projects.
LG6. Teach students the main roles and responsibilities of SCRUM, ITIL and DEVOPS as well as how these methodologies can works all together to promote IT service improvement and increase organizational productivity.
Program
This UC has the following program contents (CPs):
CP1 [Frame and Motivation]
Global vision of ITSM
CP2 [ITIL & ITSM]
Introduce the main ITSM framework: ITIL
CP3 [DEVOPS]
Introduce DEVOPS methodology and respective practices
CP4 [ITIL & DEVOPS]
Explain how DEVOPS and ITIL can work together to improve the ITSM
CP5 [SCRUM]
Introduce and explain SCRUM. Detail its content and elements as well as their meaning and field of application.
CP6 [SCRUM & ITSM]
Explain how SCRUM and ITSM relate. Plus, detail the advantages of using SCRUM in ITSM projects.
CP7 [Applicational Architecture]
Explain how the approached methodologies can work all together aiming to both improve ITSM efficiency and improve ITSM project success.
Evaluation process
This curriculum unit does not have an exam. Its practical approach is assessed by a project.
Evaluation throughout the semester:
Group assignment
Part1 (P1) - 40% of the grade
Part2 (P2) - 40% (first season)
Individual presentation (IP) - 20% (first season)
Formula::
Final grade = (P1*0,4+P2*0,4 + IP*0,2)
The students can:
Second season: improve their IA or deliver a new project for 100% of the grade (individual assignment without oral discussion)
Special season: deliver a new project for 100% of the grade (individual assignment without oral discussion)
Bibliography
Mandatory Bibliography
Title: Slides de GPA, Rúben Pereira, disponíveis na plataforma e-learning
The Unicorn Project; Gene Kim; 2019
The Phoenix Project; Kevin Behr, George Spafford and Gene Kim; 2013
DevOps for Dummies; Emily Freedom; 2019
ITIL Foundation: itil4; Stationery Office; 2019
The SCRUM Guide; Ken Schwaber and Jeff Sutherland; 2013
Authors:
Reference:
Year:
Optional Bibliography
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03725 |
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Faculty
Objectives
To succeed in this course the student should be able to:
OA1: Identify the most suited strategies for the problem to be solved.
OA2: Design and implement the needed algorithms for the intended solution.
OA3: Analyse the complexity of diverse algorithms and understand what are the implications of its usage in real problems.
OA4: Learn the main algorithms and data structures used in graphs.
Program
The syllabus contents are:
CP1: Analysis of algorithms and Complexity theory: amortized cases and approximation algorithms.
CP2: Algorithm design techniques: incremental, divide-and-conquer, randomization, greedy, dynamic programming.
CP3: Graphs: efficient data structure and algorithms (spanning trees, traversals, shortest paths, flow algorithms).
Evaluation process
Assessment can be done throughout the semester or through a final exam:
Assessment throughout the semester: E x 0.20 + T x 0.60 + M x 0.20 = 100%.
(E) Weekly exercise assignments:
- Subject up to the last lesson given.
- No minimum passing grade.
(T) Tests:
- 2 (equally weighted) individual written tests with a minimum passing grade of 7.5;
- 1st test: in the mid-term week;
- 2nd test: on the day of the first exam.
(M) Mini-projects:
- Performed in a group of 2 students.
- No minimum passing grade.
Exam: 1st, 2nd and Special Seasons (written exam) = 100%.
Bibliography
Mandatory Bibliography
Title: Cormen, Thomas, Charles Leiserson, Ronald L. Rivest and Clifford Stein (2022), Introduction to Algorithms. 34th ed., MIT Press.
John Kleinberg Eva Tardos (2005) Algorithm Design, Addison-Wesley.
Tim Roughgarden (2022). Algorithms Illuminated: Omnibus Edition. Cambridge: CUP.
Authors:
Reference:
Year:
Optional Bibliography
Title: David Williamson, David Shmoys (2010) The Design of Approximation Algorithms, Cambridge University Press.
Authors:
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Year:
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03725 |
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Faculty
Objectives
To succeed in this course the student should be able to:
OA1: Identify the most suited strategies for the problem to be solved.
OA2: Design and implement the needed algorithms for the intended solution.
OA3: Analyse the complexity of diverse algorithms and understand what are the implications of its usage in real problems.
OA4: Learn the main algorithms and data structures used in graphs.
Program
The syllabus contents are:
CP1: Analysis of algorithms and Complexity theory: amortized cases and approximation algorithms.
CP2: Algorithm design techniques: incremental, divide-and-conquer, randomization, greedy, dynamic programming.
CP3: Graphs: efficient data structure and algorithms (spanning trees, traversals, shortest paths, flow algorithms).
Evaluation process
Assessment can be done throughout the semester or through a final exam:
Assessment throughout the semester: E x 0.20 + T x 0.60 + M x 0.20 = 100%.
(E) Weekly exercise assignments:
- Subject up to the last lesson given.
- No minimum passing grade.
(T) Tests:
- 2 (equally weighted) individual written tests with a minimum passing grade of 7.5;
- 1st test: in the mid-term week;
- 2nd test: on the day of the first exam.
(M) Mini-projects:
- Performed in a group of 2 students.
- No minimum passing grade.
Exam: 1st, 2nd and Special Seasons (written exam) = 100%.
Bibliography
Mandatory Bibliography
Title: Cormen, Thomas, Charles Leiserson, Ronald L. Rivest and Clifford Stein (2022), Introduction to Algorithms. 34th ed., MIT Press.
John Kleinberg Eva Tardos (2005) Algorithm Design, Addison-Wesley.
Tim Roughgarden (2022). Algorithms Illuminated: Omnibus Edition. Cambridge: CUP.
Authors:
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Optional Bibliography
Title: David Williamson, David Shmoys (2010) The Design of Approximation Algorithms, Cambridge University Press.
Authors:
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03706 |
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Faculty
Objectives
After the course, the student will be able to:
LO1. Understand sorting and search algorithms appropriate to computational solutions;
LO2. Identify, rewrite and review common ways of organizing data and associated algorithms (with and without dynamic memory management, with iterative or recursive algorithms);
LO3. Estimate and value the complexity of algorithms on alternative data structures,
LO4. Prototype new forms of organization of data and associated algorithms suited to solve new computational problems.
Program
PC1. The problem Union-Find
PC2. Analysis of Algorithms
PC3. Stacks, Queues, Lists, Bags
PC4. Priority Queues
PC5. Mergesort Elementary Symbol Tables
PC6. Quicksort Balanced Search Trees
PC7. Hash Tables
PC8. Elementary Sorts: Selectionsort; Insertionsort; Shellsort
PC9. Advanced Sorts: Mergesort; Quicksort; Heapsort
PC10. Sorting Complexity
Evaluation process
Assessment throughout the semester: 10 individual programming exercises (25%), without a minimum grade and delivered weekly and two written tests (75%), the first in the middle of the semester and the second coinciding with the 1st season exam. Each of the written tests has a minimum grade of 7.5 points. Attendance in classes is not mandatory.
or
Individual final exam (100%) – 1st season, 2nd season and Special Season
Bibliography
Mandatory Bibliography
Title: (Algorithms, Part I - MOOC in www.coursera.org)
R. Sedgewick and K. Wayne, Algorithms, 4th edition, Addison-Wesley, 2012
Authors:
Reference:
Year:
Optional Bibliography
Title: D. Harel, Algorithmics: the Spirit of Computing, 3th edition, Addison-Wesley, 2004
F. Santos and C. Conti, Algoritmos e Estruturas de Dados - Exercícios, ISCTE-IUL, 2022.
Authors:
Reference:
Year:
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03706 |
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Faculty
Objectives
After the course, the student will be able to:
LO1. Understand sorting and search algorithms appropriate to computational solutions;
LO2. Identify, rewrite and review common ways of organizing data and associated algorithms (with and without dynamic memory management, with iterative or recursive algorithms);
LO3. Estimate and value the complexity of algorithms on alternative data structures,
LO4. Prototype new forms of organization of data and associated algorithms suited to solve new computational problems.
Program
PC1. The problem Union-Find
PC2. Analysis of Algorithms
PC3. Stacks, Queues, Lists, Bags
PC4. Priority Queues
PC5. Mergesort Elementary Symbol Tables
PC6. Quicksort Balanced Search Trees
PC7. Hash Tables
PC8. Elementary Sorts: Selectionsort; Insertionsort; Shellsort
PC9. Advanced Sorts: Mergesort; Quicksort; Heapsort
PC10. Sorting Complexity
Evaluation process
Assessment throughout the semester: 10 individual programming exercises (25%), without a minimum grade and delivered weekly and two written tests (75%), the first in the middle of the semester and the second coinciding with the 1st season exam. Each of the written tests has a minimum grade of 7.5 points. Attendance in classes is not mandatory.
or
Individual final exam (100%) – 1st season, 2nd season and Special Season
Bibliography
Mandatory Bibliography
Title: (Algorithms, Part I - MOOC in www.coursera.org)
R. Sedgewick and K. Wayne, Algorithms, 4th edition, Addison-Wesley, 2012
Authors:
Reference:
Year:
Optional Bibliography
Title: D. Harel, Algorithmics: the Spirit of Computing, 3th edition, Addison-Wesley, 2004
F. Santos and C. Conti, Algoritmos e Estruturas de Dados - Exercícios, ISCTE-IUL, 2022.
Authors:
Reference:
Year:
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03706 |
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Faculty
Objectives
After the course, the student will be able to:
LO1. Understand sorting and search algorithms appropriate to computational solutions;
LO2. Identify, rewrite and review common ways of organizing data and associated algorithms (with and without dynamic memory management, with iterative or recursive algorithms);
LO3. Estimate and value the complexity of algorithms on alternative data structures,
LO4. Prototype new forms of organization of data and associated algorithms suited to solve new computational problems.
Program
PC1. The problem Union-Find
PC2. Analysis of Algorithms
PC3. Stacks, Queues, Lists, Bags
PC4. Priority Queues
PC5. Mergesort Elementary Symbol Tables
PC6. Quicksort Balanced Search Trees
PC7. Hash Tables
PC8. Elementary Sorts: Selectionsort; Insertionsort; Shellsort
PC9. Advanced Sorts: Mergesort; Quicksort; Heapsort
PC10. Sorting Complexity
Evaluation process
Assessment throughout the semester: 10 individual programming exercises (25%), without a minimum grade and delivered weekly and two written tests (75%), the first in the middle of the semester and the second coinciding with the 1st season exam. Each of the written tests has a minimum grade of 7.5 points. Attendance in classes is not mandatory.
or
Individual final exam (100%) – 1st season, 2nd season and Special Season
Bibliography
Mandatory Bibliography
Title: (Algorithms, Part I - MOOC in www.coursera.org)
R. Sedgewick and K. Wayne, Algorithms, 4th edition, Addison-Wesley, 2012
Authors:
Reference:
Year:
Optional Bibliography
Title: D. Harel, Algorithmics: the Spirit of Computing, 3th edition, Addison-Wesley, 2004
F. Santos and C. Conti, Algoritmos e Estruturas de Dados - Exercícios, ISCTE-IUL, 2022.
Authors:
Reference:
Year:
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03706 |
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Faculty
Objectives
After the course, the student will be able to:
LO1. Understand sorting and search algorithms appropriate to computational solutions;
LO2. Identify, rewrite and review common ways of organizing data and associated algorithms (with and without dynamic memory management, with iterative or recursive algorithms);
LO3. Estimate and value the complexity of algorithms on alternative data structures,
LO4. Prototype new forms of organization of data and associated algorithms suited to solve new computational problems.
Program
PC1. The problem Union-Find
PC2. Analysis of Algorithms
PC3. Stacks, Queues, Lists, Bags
PC4. Priority Queues
PC5. Mergesort Elementary Symbol Tables
PC6. Quicksort Balanced Search Trees
PC7. Hash Tables
PC8. Elementary Sorts: Selectionsort; Insertionsort; Shellsort
PC9. Advanced Sorts: Mergesort; Quicksort; Heapsort
PC10. Sorting Complexity
Evaluation process
Assessment throughout the semester: 10 individual programming exercises (25%), without a minimum grade and delivered weekly and two written tests (75%), the first in the middle of the semester and the second coinciding with the 1st season exam. Each of the written tests has a minimum grade of 7.5 points. Attendance in classes is not mandatory.
or
Individual final exam (100%) – 1st season, 2nd season and Special Season
Bibliography
Mandatory Bibliography
Title: (Algorithms, Part I - MOOC in www.coursera.org)
R. Sedgewick and K. Wayne, Algorithms, 4th edition, Addison-Wesley, 2012
Authors:
Reference:
Year:
Optional Bibliography
Title: D. Harel, Algorithmics: the Spirit of Computing, 3th edition, Addison-Wesley, 2004
F. Santos and C. Conti, Algoritmos e Estruturas de Dados - Exercícios, ISCTE-IUL, 2022.
Authors:
Reference:
Year:
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03706 |
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Faculty
Objectives
After the course, the student will be able to:
LO1. Understand sorting and search algorithms appropriate to computational solutions;
LO2. Identify, rewrite and review common ways of organizing data and associated algorithms (with and without dynamic memory management, with iterative or recursive algorithms);
LO3. Estimate and value the complexity of algorithms on alternative data structures,
LO4. Prototype new forms of organization of data and associated algorithms suited to solve new computational problems.
Program
PC1. The problem Union-Find
PC2. Analysis of Algorithms
PC3. Stacks, Queues, Lists, Bags
PC4. Priority Queues
PC5. Mergesort Elementary Symbol Tables
PC6. Quicksort Balanced Search Trees
PC7. Hash Tables
PC8. Elementary Sorts: Selectionsort; Insertionsort; Shellsort
PC9. Advanced Sorts: Mergesort; Quicksort; Heapsort
PC10. Sorting Complexity
Evaluation process
Assessment throughout the semester: 10 individual programming exercises (25%), without a minimum grade and delivered weekly and two written tests (75%), the first in the middle of the semester and the second coinciding with the 1st season exam. Each of the written tests has a minimum grade of 7.5 points. Attendance in classes is not mandatory.
or
Individual final exam (100%) – 1st season, 2nd season and Special Season
Bibliography
Mandatory Bibliography
Title: (Algorithms, Part I - MOOC in www.coursera.org)
R. Sedgewick and K. Wayne, Algorithms, 4th edition, Addison-Wesley, 2012
Authors:
Reference:
Year:
Optional Bibliography
Title: D. Harel, Algorithmics: the Spirit of Computing, 3th edition, Addison-Wesley, 2004
F. Santos and C. Conti, Algoritmos e Estruturas de Dados - Exercícios, ISCTE-IUL, 2022.
Authors:
Reference:
Year:
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02864 |
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Faculty
Objectives
At the end of this course, students should be able:
OA1: understand and identify problems involving mining massive datasets
OA2: to apply supervised and non-supervised learning methods to Big Data
OA3: to understand diferent recomendation systems techniques
OA4: to know how to analyse data streams
OA5: to understand what is Deep Learning and its techniques
OA6: to know how to compute frequent itemsets and association rules
OA7: to understand graph processing techniques
Program
CP1 Big data foundations
CP2 Large scale supervised and unsupervised learning
CP3 Recommender systems
CP4 Mining data streams
CP5 Introduction to deep learning
CP6 Frequent itemsets and association rules
CP7 Link analysis and mining social-networks graphs
Evaluation process
This course includes the following assessment methods: (1) assessment throughout the semester; (2) assessment by exam.
(1) Assessment throughout the semester
The final grade is made up of:
- Individual written test (70%), with a minimum mark of 8.0;
- Group work (30%).
The group work has a mid-term submission, which will count for 30%, and a submission at the end of the semester, which will count for 70%. Those who do not submit the mid-term portion will automatically be assessed by exam.
The work will include an oral presentation/discussion, and the final grade will be individual.
(2) assessment by exam
The final grade will be based on a single written exam, including special season.
Bibliography
Mandatory Bibliography
Title: Deep Learning, Ian Goodfellow and Yoshua Bengio, 2016, MIT Press.
Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale, Ofer Mendelevitch, Casey Stella and Douglas Eadline, Addison-wesley, 2016.
Advanced Analytics with Spark: Patterns for Learning from Data at Scale, Sandy Ryza et al., O'Reilly Media, 2017.
Learning Spark: Lightning-Fast Big Data Analysis, Holden Karau, A. Konwinski, P. Wendell and M. Zaharia, O'Reilly Media, 2015.
Big Data: Algorithms, Analytics, and Applications, Kuan-Ching Li et al., Chapman and Hall/CRC, 2015.
Mining of Massive Datasets, A. Rajaraman, J. Ullman, 2011, Cambridge University Press.
Authors:
Reference:
Year:
Optional Bibliography
Title: The elements of statistical learning, Trevor Hastie, Robert Tibshirani, and Jerome Friedman. Springer, 2001.
All of Statistics: A concise course in Statistical Inference, L.Wasserman, Springer, 2003.
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L5087 |
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Faculty
Objectives
At the end of the this UC, the student must:
OA1. Know and use the key concepts of visual anthropology.
OA2. Understand ways to see and look as forms of knowledge production, framed by anthropological and ethnographic practice and knowledge
OA3. Distinguish image uses and approaches in visual Anthropology (positivism, realism, direct, observational and participatory cinema)
OA4. Be able to work with image-editing program and sound (laboratories)
OA5. Interpret and produce visual representations with ethnographic approach (introdutory)
Program
1. Introduction: the use of visual tools in Anthropology
a) the visible and the invisible, the sensorial and the rational
b) criticising the notion of representation
c) imaginary and his 'voices'
d) the uses of illustration in Anthropology: drawing, photography, film, website and soundlandscapes
2. Practices of seeing
a) age of mechanical reproductiblity of images
b) the modern scope regimes
c) spectacular society
3. Ways of seeing, ways of making: how documentaries are designed
a) the city and the production of images
b) installation, podcast and interactive digital platform
c) the imperialism of seeing and participatory and militant cinema
4. Visual Anthropology and Visual Digital Cultures
5. Production of final portfolio on proposed issues (empirical and experimental exercises)
Evaluation process
Assessment will be based on:
Assessment during the semestre:
a) Attendance and participation in exercises, classes and seminars (20%);
b) Individual review essay (max. 3 pag.: 20%)
c) Portfolio of exercises and final report up to 5 p. (60%) - The Portfolio is made up of exercises in visual narratives, podcasts and photo-elicitation/ethnofiction and a report that draws together the learning experienced, the readings carried out and reflects on the productions presented in the Portfolio.
The course takes place in a laboratory workshop, so student attendance and participation is a fundamental part of the assessment, and a minimum of 70% attendance at laboratory sessions is required.
Assessment by exam:
Students who do not attend the course during the semester they have an exam. Students are successful in the course if they achieve a mark of 10 or more, if they do not achieve that mark they will also have an examination system regulated by ISCTE-IUL's general pedagogical regulations.
Bibliography
Mandatory Bibliography
Title: Andrade, Rosane de ,2002, Fotografia e Antropologia. olhares fora-dentro, S.Paulo EDUC/FAPESP/Estaçaod a Libedade
Banks, Marcus & Howard Morphy (ed.), 1999 (1997), Rethinking Visual Anthropology, New Haven: Yale University Press
Edwards, Elizabeth (ed.), 1992, Anthropology and Photography 1860-1920, New Haven & London: Yale University Press & The Royal Anthropological Institute
Feldman-Bianco, bela e Míriam Moreira-Leite(orgs) 2006 Desafios da Imagem, Campinas, Papírus
Hockings, Paul (ed), 1995, Principles of Visual Anthropology, Berlin & New York: Mouton de Gruyter.
Ribeiro, José da Silva, 2004, Antropologia Visual. Da minúcia do olhar ao olhar distanciado, Lisboa, Edições Afrontamento.
Authors:
Reference:
Year:
Optional Bibliography
Title: Andrade, Rosane de ,2002, Fotografia e Antropologia. olhares fora-dentro, S.Paulo EDUC/FAPESP/Estaçaod a Libedade
Banks, Marcus & Howard Morphy (ed.), 1999 (1997), Rethinking Visual Anthropology, New Haven: Yale University Press
Collier,John,Jr.; Collier, Malcolm (posfácio de Edward T. Hall), 1996 (1986), Visual Anthropology: Photography as a Research Method (Revised and Expanded Edition), Albuquerque: University of New Mexico Press
Edwards, Elizabeth (ed.), 1992, Anthropology and Photography 1860-1920, New Haven & London: Yale University Press & The Royal Anthropological Institute
Hockings, Paul (ed), 1995, Principles of Visual Anthropology, Berlin & New York: Mouton de Gruyter.
Landau, Paul & Deborah D. Kaspin (ed.), 2002, Images and Empires. Visuality in colonial and postcolonial Africa, Berkeley e Los Angeles, University of California Press.
Lutz, Catherine A. & Jane L. Collins, 1993, Reading National Geographic, Chicago, The University of Chicago Press
Pink, Sarah, 2001, Doing Visual Ethnography, London, Sage
Ribeiro, José da Silva, 2004, Antropologia Visual. Da minúcia do olhar ao olhar distanciado, Lisboa, Edições Afrontamento.
Authors:
Reference:
Year:
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L0731 |
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Faculty
Objectives
After completing the course, students should
(LO1) be aware of the advantages and challenges of using and developing AI based systems and models, in particular search algorithms, knowledge representation and reasoning, approaches for adaptive systems, and machine learning;
(LO2) be capable of identifying the requirements of the systems and models to create;
(LO3) be capable of choosing and the approaches more suited to the LO2 requirements
(LO4) mastering and usage of the approaches presented in the course for system development and world modelling
Program
(CP1) Fundamental notions of AI with emphasis on the search-based approach
(CP2) Search algorithms: depth first and breadth first, A*
(CP3) The basics of machine learning: supervised, reinforcement learning and unsupervised learning
(CP4) Genetic algorithms
(CP5) Multilayer feedforward neural networks with backpropagation
(CP6) Fundamental notions relating to knowledge, representation and the architecture of knowledge-based systems
(CP7) First-order predicate logic: representation and deduction
(CP8) Declarative knowledge represented in Logic Programming
(CP9) Rule Systems based on Fuzzy Logic
Evaluation process
Assessment throughout the semester:
- 2 Tests (35% each), minimum grade of 8.5 in each test
- 2 Project (15% each) minimum grade of 9.5 in each project
Final evaluation:
- Exam (in 3 possible dates: 1ª época, 2ª época and Special Season) 100%
The final oral discussions of the projects take place in groups after the final submission, on the date(s) indicated in its statement. First project is due in mid semester and the second in the last week of classes. Although the projects are developed in a group, the grade awarded to each student in the group is individualized depending on the student's contribution to the project and the student's performance in the oral discussion
The tests and the Exams may have groups of questions with a minimum grade
To access the tests and exam, it is necessary to complete all activities related to the covered topics up to this moment on Moodle.
Students may be required to explicitly enroll in any of the evaluation components
Bibliography
Mandatory Bibliography
Title: A cadeira assenta fundamentalmente nos apontamentos para as aulas sobre Sistemas Baseados em Conhecimento, e nos livros [Russell e Norvig 2003] sobre Inteligência Artificial, [Clocksin e Mellish 1994] sobre Prolog, e [Graham 1996] sobre LISP.
Clocksin, W.F. e Mellish, C.S. 2003. Programming in Prolog Using the ISO Standard(Quinta Edição). Springer Verlag (existe na biblioteca, embora seja a quarta edição).
Russell, S.; e Norvig, P. 2003. Artificial Intelligence: a Modern Approach, Prentice Hall. Capítulos 3 a 9. (existente na biblioteca).
Graham, P. 1996. ANSI Common Lisp. PrenticeHall.
Authors:
Reference:
Year:
Optional Bibliography
Title: Linguagem de Programação Prolog
Bratko, I. 1990. Prolog Programming for Artificial Intelligence. Addison Wesley Publishing Company (existente na biblioteca).
Lógica de Predicados e Forma Clausal
Michael R. Genesereth, Nils J. Nislsson. 1987. ?Logical Foundations of Artificial Intelligence?. Morgan Kaufman Publishers (Capítulos 2, 3 e 4)
Sistemas Baseados em Conhecimento (Perspectiva teórica)
- Ronald Brachman, Hector Levesque. 2004. "Knowledge Representation and Reasoning". Morgan Kaufmann
- Mark Stefik. 1995. Introduction to Knowledge Systems?. Morgan Kaufmann
Authors:
Reference:
Year:
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L0731 |
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Faculty
Objectives
After completing the course, students should
(LO1) be aware of the advantages and challenges of using and developing AI based systems and models, in particular search algorithms, knowledge representation and reasoning, approaches for adaptive systems, and machine learning;
(LO2) be capable of identifying the requirements of the systems and models to create;
(LO3) be capable of choosing and the approaches more suited to the LO2 requirements
(LO4) mastering and usage of the approaches presented in the course for system development and world modelling
Program
(CP1) Fundamental notions of AI with emphasis on the search-based approach
(CP2) Search algorithms: depth first and breadth first, A*
(CP3) The basics of machine learning: supervised, reinforcement learning and unsupervised learning
(CP4) Genetic algorithms
(CP5) Multilayer feedforward neural networks with backpropagation
(CP6) Fundamental notions relating to knowledge, representation and the architecture of knowledge-based systems
(CP7) First-order predicate logic: representation and deduction
(CP8) Declarative knowledge represented in Logic Programming
(CP9) Rule Systems based on Fuzzy Logic
Evaluation process
Assessment throughout the semester:
- 2 Tests (35% each), minimum grade of 8.5 in each test
- 2 Project (15% each) minimum grade of 9.5 in each project
Final evaluation:
- Exam (in 3 possible dates: 1ª época, 2ª época and Special Season) 100%
The final oral discussions of the projects take place in groups after the final submission, on the date(s) indicated in its statement. First project is due in mid semester and the second in the last week of classes. Although the projects are developed in a group, the grade awarded to each student in the group is individualized depending on the student's contribution to the project and the student's performance in the oral discussion
The tests and the Exams may have groups of questions with a minimum grade
To access the tests and exam, it is necessary to complete all activities related to the covered topics up to this moment on Moodle.
Students may be required to explicitly enroll in any of the evaluation components
Bibliography
Mandatory Bibliography
Title: A cadeira assenta fundamentalmente nos apontamentos para as aulas sobre Sistemas Baseados em Conhecimento, e nos livros [Russell e Norvig 2003] sobre Inteligência Artificial, [Clocksin e Mellish 1994] sobre Prolog, e [Graham 1996] sobre LISP.
Clocksin, W.F. e Mellish, C.S. 2003. Programming in Prolog Using the ISO Standard(Quinta Edição). Springer Verlag (existe na biblioteca, embora seja a quarta edição).
Russell, S.; e Norvig, P. 2003. Artificial Intelligence: a Modern Approach, Prentice Hall. Capítulos 3 a 9. (existente na biblioteca).
Graham, P. 1996. ANSI Common Lisp. PrenticeHall.
Authors:
Reference:
Year:
Optional Bibliography
Title: Linguagem de Programação Prolog
Bratko, I. 1990. Prolog Programming for Artificial Intelligence. Addison Wesley Publishing Company (existente na biblioteca).
Lógica de Predicados e Forma Clausal
Michael R. Genesereth, Nils J. Nislsson. 1987. ?Logical Foundations of Artificial Intelligence?. Morgan Kaufman Publishers (Capítulos 2, 3 e 4)
Sistemas Baseados em Conhecimento (Perspectiva teórica)
- Ronald Brachman, Hector Levesque. 2004. "Knowledge Representation and Reasoning". Morgan Kaufmann
- Mark Stefik. 1995. Introduction to Knowledge Systems?. Morgan Kaufmann
Authors:
Reference:
Year:
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L0731 |
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