Babes-Bolyai University of Cluj-Napoca
Faculty of Mathematics and Computer Science
Study Cycle: Master
SUBJECT

Code	Subject	
MI360	Cooperative Intelligent Agents	

Section	Semester	Hours: C+S+L	Category	Type	
Intelligent Systems - in English	1	2+2+0		compulsory	

Teaching Staff in Charge	Assoc.Prof. SERBAN Gabriela, Ph.D., gabis@cs.ubbcluj.ro	
Aims	To introduce the student a new field of Artificial Intelligence - Distributed AI. To allow a comparative approach of theoretical aspects in distributed and classic AI. To present the field of Intelligent Agents as a new research and application domain of Artificial Intelligence. To contribute to understanding the necessity of DAI through the study of relevant industrial and practical applications.	
Content	1. Introduction  
- Distributed Artificial Intelligence
- The concept of agent and intelligent agent
2. Intelligent Agents 
- Definitions, properties, taxonomies
- Abstract and concrete architectures for intelligent agents
- Software agents
- Mobile agents, interface agents
- Application domains
- Agents and Objects
- Agents and Expert Systems
- Agent based software engineering
3. Multiagent systems and societies of agents 
- Coordination, cooperation, communication - protocols
- Negotiation
- Communication languages between agents
- KQML, FIPA-ACL
4. Distributed problem solving and planning 
- Distributed problem solving
- Example of distributed problems
- Planning techniques
- Distributed planning
5. Search algorithms for agents 
- Distributed constraint satisfaction problems
- Asynchronous backtracking
- Distributed path finding problems
- Asynchronous dynamic programming
- Learning Real Time A*
- Bidirectional search algorithm
- Real time multiagent search algorithm 
- Two player games
6. Applications of agents and multiagent systems 
- Intelligent agents in e-business and e-commerce
- Intelligent agents in e-banking
- Intelligent agents for Distributed Data Mining
- Information agents
- Intelligent agents in software engineering 
- Ant systems
7. Learning in multiagent systems 
- Types of learning
- Cooperative learning in multiagent systems
- Team learning
- Concurrent learning
- Learning and communication
- Learning and coordination
- The credit assignment problem
- Application domains for multiagent learning
8. Formal methods in Distributed Artificial Intelligence 
- Logical fundaments in the multiagent systems theory
- Propositional and predicate logic
- Modal logic
- Deontic logic
- Dynamic logic
- Temporal logic
- Nonmonotonic logics
- Cognitive primitives in formalizing agent based systems
9. Industrial and practical applications of Distributed Artificial Intelligence 
- Where in the products life cycle can be used agents
- The advantages of using agents
- Methods for developing agent based applications
- Instrumente de dezvoltare a aplicaţiilor bazate pe agenţi
	
Bibliography	1. SERBAN, GABRIELA: Sisteme multiagent in Inteligenta Artificiala Distribuita. Arhitecturi si aplicatii. Ed. RisoPrint, Cluj-Napoca, 2006
2. SERBAN, GABRIELA, POP, H.F., Tehnici de Inteligenţă Artificială. Abordări bazate pe Agenţi Inteligenţi, Ed. Mediamira, Cluj-Napoca, 2004 
3. WEISS, GERHARD (Ed.): Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, MIT Press, 1999.
4. RUSSELL, J.S, NORVIG, P., Artificial Intelligence- A Modern Approach, Prentice- Hall, Inc., New Jersey, 1995 
5. WOOLDRIDGE, MICHAEL: Agent-Based Software Engineering. London: Mitsubishi Electric Digital Library Group, 1997. 
6. SHOHAM, YOAV: Agent-oriented programming. Artificial Intelligence. 60(1), 1993, pp.51-92.
	
Assessment	The activity ends with a written final exam (grade E). During the semester, the students will have to prepare two theoretical reports (grades R1, R2) and a practical project that will have to illustrate the importance of using intelligent agents on a specific task (grade P). The students activity during the semester will be also considered (grade A).  The final grade is the weighted mean of the five grades mentioned above. The final grade = 40%E + 15%R1 + 15%R2 + 20%P + 10%A. Students who demonstrate excellent research performance by developing the project to publication will get an extra score of 10% from the final grade. Successful passing of the exam is conditioned by the final grade that has to be at least 5.