1. Algorithmic, Game-theoretic and Logical Foundations
Computer Science & Engineering, University of Nevada, Reno
CS483/683 - AI Programming
Multi-Agent Systems:
Algorithmic, Game-theoretic and Logical Foundations
Lecture 1:
Introduction to
Multi-Agent Systems
19 January 2010
Instructor: Kostas Bekris

2. What are multi-agent systems
Very vague definition:
A system composed of multiple interacting intelligent agents
Multiple?
Intelligent Agent?
Interacting?

3. Intelligent Agents
How can we fully describe an AI problem?

4. Multiple Interacting Agents

5. Forms of Interaction Treat other agents similarly to the environment:
Sensing and observing the behavior of other agents
Acting upon other agents
Aspects of interaction in the field of multi-agent systems:
Reason about the decision-making process of other agents
Communication
Respect predefined “social laws” and protocols of interaction
how can a team of agents make fair decisions (e.g., voting schemes)

6. Multi-Agent System Cooperative Agents (optimize a common utility)
Agent Relations
Multi-Agent System
Cooperative Agents
(optimize a
common utility)
Non-cooperative Agents
(separate utilities)
Coalitional Agents
(e.g. opposing teams
of agents)
Competing Agents
(e.g., opposing utilities)
Agents with
diverging interests

7. Types of Problems Agent Design Mechanism Design
How to design an agent that collaborates with other agents to solve a common task?
How to design an agent that competes with other agents so as to be the winner?
How to design an agent that operates efficiently in an environment where multiple other agents operate with divergent interests?
Mechanism Design
How to design the entire system so that a common utility function is optimized even when each agent is “strategic” (i.e., aims to optimize its own utility?)

8. Topics of Research in MAS
Agent-oriented Software Engineering
Beliefs, Desired and Intentions (BDI)
Cooperation and Coordination
Organization
Communication
Negotiation
Distributed Problem Solving
Multi-Agent Learning
Scientific Communities
Dependability and Fault-Tolerance

9. Example Applications Autonomous Physical Devices
Multi-robot teams
Coordinated Defense / Space Exploration Systems
Sensor Networks
Transportation and Traffic
Simulation Environments
Computer Games
Scientific Simulation
Networking, Mobile Technologies and the Internet
Automatic and Dynamic Load Balancing
Self-healing networks
Financial / Economics problems
Pricing, accounting and logistics
Bidding mechanisms, negotiations, e-commerce, electricity/energy markets

10. Why do we need MAS? Ubiquity Fault-tolerance
Send sensors and robots everywhere
Fault-tolerance
Make many small, cheap devices, instead of one large, expensive one
If a single device fails, the system may continue operating
The real world is a huge Multi-Agent System
We might have to simulate real-world MAS
Or we might desire to exercise some control over them
For fun
Computer games and games in general
For profit
You have to compete to succeed
And you have to understand the underlying MAS to be a good competitor

11. Objections to MAS Isn’t it all just Distributed Systems / Networking?
Systems can be self-interested
Isn’t is all just Artificial Intelligence?
Communication and social aspects were typically ignored in classical AI
Isn’t it all just Economics / Game Theory?
We must also come with algorithmic solutions to game theoretic problems
Not all assumptions in Game Theory are always true (e.g., “perfect market”)
Isn’t it all Social Science?
Artificial societies do not have to be built exactly like human and biological societies

12. Class Overview Intro to Multi-Agent Systems Distributed Path Planning
Distributed Constraint Satisfaction
Distributed Constraint Optimization
Belief Propagation
ADOPT
Auctions
Coordination through Social Laws
and protocols ∞ ∞ 2 a d 1 1 2 ∞ s t 1 1 3 3 b c 2 ∞ ∞
{red, blue, green} ≠ ≠ ≠
{red, blue, green}
{red, blue, green}

13. Proposal Presentation
Class Overview
Games in Normal Form
Two-player, zero-sum games
General-sum games
Nash equilibria and strategies
Games in Extensive Form
Perfect-Information Games
Imperfect Information
Behavioral Strategies
Richer representations of games
Bayesian games
Communication and Signaling games
Multi-agent Resource Allocation
Auctions
Husband
Wife
Lethal
Weapon
Wondrous
Love
2, 1
0, 0
1, 2
Early March:
Proposal Presentation
and Report
Late April:
Final Presentation