After a general introduction to Multi-Agent Systems (appropriate chapters in Russell/Norvig, Artificial Intelligence, Prentice Hall, 1995) in the first lecture, we consider in Chapters 2--5 general techniques of
Chapter 1: | Introduction and
Terminology (1 Lecture) We illustrate the difference between Multi-Agent Systems and classical distributed AI, give a first definition and introduce in the terminology. 1.1 General: Distributed AI I vs. Multi-Agentsystems. 1.2 Intelligent Agents: Intelligent interactive Agents, Definition of an Agent, Properties of the environment, reactive/proactive/social, Agent vs. Object-Orientation, PAGE-Description. 1.3 Mathematical Definitions: Abstract View of an agent: mathematical functions action: S* --> A, env: SxA --> Pot(S), hist, see: S --> P, next: IxP --> I. Get Slides |
Chapter 2: | Fundamental Architectures:
(1 Lecture) We illustrate three main agent architectures. 2.1 Reactive Agents: Formal Model, Behaviour, Inhibition Relation, Complexity, Pro/Contra, Example: Polar Lander, Cooperative Programming, 2.2 BDI-Agents: Sture vs Unsichere Agenten (Factor gamma), BDI-Structure 2.3 Layered Architectures: Fig. 2.1 [Fig. 1.6 on p. 62], Touring Machine Fig. 2.2 [Fig. 1.7 on p. 63], Autonomous Vehicle, Planning/Modelling/Control Layers, Interrap: Fig. 2.3 [Fig. 1.8 on p. 65] Get Slides |
Chapter 3: | Logic Based Architectures:
(1 Lecture) We illustrate logic based architectures. Symbolic AI, Agent as Theorem Prover, Database as internal state, 3.1 Wumpus World in Sentential Logic 3.2 The Situation Calculus: Situation-calculus, result-terms, fluents, memory-predicate At(,,,), 3.3 Problems Qualification-Problem, nonmonotonic logics, Frame-Problem, 3.4 A Solution to the Frame Problem? Successor-State Axioms: Automatic Generation and Reduction of their number: #A + #F instead of #A x #F. Get Slides |
Chapter 4: | Distributed Decision Making
(2 Lectures) We consider the most important techniques for decision making: Voting, auctions and Bargaining. 4.1 Evaluation Criteria: Social welfare, Pareto Efficiency, Individuel Rational, Stability: Nash Equilibrium. 4.2 Voting: Arrows Theorem, Ways out, Binary Protocol: Fig. 4.1 [Fig 5.1 on p. 206], Borda Protocol: Fig. 4.2 [Table 5.2 on p. 206]. 4.3 Auctions: (4 Typs (first price open cry--second price sealed bid), private/common/correlated value, Dominant Strategies, Profit for the Auktioneer, Non optimal allocations, Lying and Counterspeculation at Vickrey, Lookahead). 4.4 Bargaining: axiomatic/strategic, Discountfactor: Table 4.1 [Table 5.4 on p. 222], Table 4.2 [Table 5.5 on p. 222], bargaining costs. Get Slides |
Chapter 5: | Contract Nets and
Coalition Formation (1 Lecture) Wir introduce two of the most important principles developed for Agent systems: Contract Nets (how to determine which contracts should be taken) and Coalition Formation (how to determine if and with whom agents should work together). 5.1 Contract-Nets: Tasc-Allocations Model, IR-Contract, Decision making: MC_add, MC_remove, Gradient-Descent, Maximizing social welfare, anytime Algorithm. 4 Types of Nets: O, C, S, M. Problem with local Maxima. OCSM-Contracts: Gradient-Descent without Backtracking. 5.2 Coalition Formation: Nash vs Strong Nash, 5.2.1. Coalition Formation for CFG's: Def. CFG, Super additive Games, Search through the CS-Graph: Fig. 5.1 [Fig. 5.3 on p. 244] , Approximations, Last two Layers: CS-Search 1: Fig. 5.2 [Fig. 5.4 on p. 246] Improving the bound by breadth-first search from the top, 5.2.2. Paralellization of the search:, 5.2.3. Payoff Division: 3 Axioms, Shapley-Value) Get Slides |