The course Multi-agent systems deals with development of systems with a specific kind of modularity based on agent metaphor.
MAS 2010
1. Multiagent system example. Agent metaphor. Complex system. Robustness. Decentralisation. Artificial Intelligence. Weak agents and emergence. Strong agents and AI employment. Multi-agent system. Agents classification. Communication among agents. lecture 1
2. Representation and communication language. lecture 2 (play with XSLT)
3. Representation and Commnunication Language. Implementation of MAS within network programming, OOP and IPC. Prerequisity: Transport layer of ISO OSI. Middleware. lecture 3
4. MAS as a kind of middleware. Programming on middle tier: RMI, RMI-IIOP, CORBA, WebServices(Axis). lecture 4
5. MAS as a kind of middleware. Direct communication. Programming with JADE. FIPA, ACL. AMS, DF. lecture 5
6. MAS as a kind of middleware. Indirect communication. Client-Server. Agent-Space. lecture 6
7. MAS over OO virtual machine. Multithreading. Synchronization. lecture 7
8. MAS over IPC. SRR model. Master-Slave. Client-Server. Agent-Space. lecture 8
9. MAS based control. Subsumption. lecture 9
10. Behavioral architectures. MAS-based modelling of biological systems. Failures and delusions supporting evidence of MAS organisation of living systems. lecture 10
11. Agent-Space architecture. Modelling in real-time. lecture 11
12. Incorporation of traditional AI approach to MAS. lecture 12
Training:
training 1. Prerequsities: Java
training 2. Prerequsities: VRML: statics and dynamics (Play with VRML)
training 3. Prerequsities: example of VRML scene controlled via TCP/IP: bullet collision (programming on communication tier)
training 4. Simple space implemented via RMI or CORBA (programming on middle tier)
training 5. Direct communication with JADE
training 6. Indirect communication with Agent-Space: Remote control of bullet in VRML scene via simple MAS implemented over RMI
training 7. Proprietary multi-agent system over multithreading of JVM
training 8. Programming over SRR under JavaShell
training 9. Multi-agent Control. Reimplementation of mobile robot ALLEN
training 10. Behavioral architecture for LEGO robot
training 11. Robot following ball controlled by set of heterogeneous agents
training 12. Inteligent agent controlled by reinforcement learning
| 1. | Michal Vince | 18 |
| 2. | Michal Stríženec | 17 |
| 3. | Miroslav Medveď | 15 |
| 4. | Ondrej Mikuláš | 14.5 |
| Michal Gašpierik | 14.5 | |
| 6. | Jaroslav Blanář | 13.5 |
| 7. | Petra Horňáková | 13 |
| 8. | Lukáš Bača | 12 |
Requirement:
almost 100% presence at tranings or project
ability to solve all problems demonstrated on training
Literature:
mainly lectures and my publications
Kelemen J.: Strojovia a agenty
Kubik. A.: Agenty a multiagentove systemy
This course is part of educational program at http://www.ii.fmph.uniba.sk/
Others:
Machine vision for young programmers:
pdf ppt
Evolution of programming structures
pdf ppt
Embodiment from Engineer's Point of View
pdf ppt
Hidden Markov Models
pdf ppt
Principal component analysis
pdf ppt
Subsumption architecture
pdf ppt video
pdf ppt video
How can computer recognize orange color?
pdf ppt
Color vision
pdf
Introduction to robot vision
pdf ppt training
Object mapping (lecture for course "Tvorba informačných systémov")
pdf ppt
Object Recognition: Histogram of oriented gradients (HOG) & Dominant orientation templates (DOT)
(by Michal Vician)
pdf
LEGO robots
Star from computer tape (KSP, Demacek)
Diploma thesis:
2007/08 Robosoccer by Milan Leitman video