Programming of Multi-Agent and Multi-Robot Systems


Aim of the course

To familiarize students with selected methods of modeling, design and implementation of agent systems represented as computer software or a group of cooperating robots.

Lecture programme

1. Agent system organization. 2. Mobile robots, multi-robot systems. Agent approach to multi-robot systems. Control of mobile robots, sensors, effectors, building a model of the environment, interaction with the environment, methods of communication. 3. Classical planning and planning in agent systems. STRIPS. Planning graphs. GraphPlan. DCSP. Partial Global Planning. Planning and coordination in multi-robot systems. 4t. Machine learning and learning with strengthening in agent systems and multi-robot systems. 5. Methods and algorithms for seeking solutions in agent systems. Basics of game theory. Nash equilibrium. Pareto optimality. Dominant strategy. Prisoner's dilemma. Coalitions. Contract Net. Fair: Nash and Rubinstein model. Auctions: English, Dutch, secret, Vickrey's. Commercial models. 6. Cooperation, adaptation, self-organization in agent systems and groups of mobile robots. 7. Methodologies for modeling and design of agent systems. technologies and environments, usage. 8. Environments for development and simulation of multi-turn systems.

Overview of the course elements

The course includes laboratory exercises, as well as a project to enable the practical application of acquired knowledge. Exercises deal with the implementation of a project of an agent system using existing methodologies (GAIA, Tropos, Prometheus, and others) and tools, as well as the control and coordination of groups of robots using the agent approach. During classes students use environments for development and simulation of multi-robot systems, and the kits of physical mobile robots available in the laboratory.

Reading list

1. G. Weiss (ed), Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, The MIT Press, 1999
2. Y. Shoham, K. Leyton-Brown, Multiagent Systems. Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge, 2009
3. F. Bergenti, M.-P. Gleizes, F. Zambonelli, Methodologies and Software Engineering For Agent Systems. The Agent-Oriented Software Engineering Handbook, Kluwer Academic Publishers, 2004
4. J. Liu, J. Wu, Multiagent Robotic Systems, CRC, 2001
5. J. M. Holland, Designing Autonomous Mobile Robots: Inside the Mind of an Intelligent Machine, Newnes, Elsevier, 2003

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