Automatic Synthesis & Composition of Agent Behaviors
The tutorial will survey some of the major developments in agent behavior synthesis and composition. The tutorial will cover the problem specification, the various techniques developed to solve it, and the relationship with various problems in several areas of CS and AI.
The behavior composition problem involves automatically synthesising a controller-coordinator that can implement a given desired but non-existing target complex behaviour (e.g., a home entertainment system) by using a set of available existing behaviour modules (e.g., video cameras, TVs, lights, music and game devices, etc.). A behaviour here refers to the operational logic of a system and is general represented as a transition system. This composition synthesis problem is important in that it can be recast in a variety of forms within several sub-areas of Artificial Intelligence and Computer Science, including robot ecologies and intelligent spaces, agent programming and multi-agent system, web-service composition, automated planning, among others.
Intro - Motivation, domains of applicability, areas.
Bisimulation and Simulation
Deterministic stateful service as transition systems
Agent Behavior Composition
Nondeterministic agent behaviors as transition systems
Composition by ND-simulation
Just in time, failures, parsimonious refinements
Behavior synthesis against opponent
Two player game structure and game goals
Mu-calculus for goals
Model checking game structures
Composition via 2GS Model Checking
Safety (goal) games
Composition via 2GS model checking
Relationship with LTL and ATL synthesis
Tools: TLV, MCSMAS, NuGAT
Unsolvable problems: what to do?
Supremal Realizable Target
Agent Planning Programs
Data box/planning domain
Giuseppe De Giacomo, Fabio Patrizi, Sebastian Sardiña: Automatic behavior composition synthesis. Artificial Intelligence 196: 106-142 (2013)
Giuseppe De Giacomo, Paolo Felli, Fabio Patrizi, Sebastian Sardiña: Two-Player Game Structures for Generalized Planning and Agent Composition. AAAI 2010
Nitin Yadav, Paolo Felli, Giuseppe De Giacomo, Sebastian Sardiña: Supremal Realizability of Behaviors with Uncontrollable Exogenous Events. IJCAI 2013
Nitin Yadav, Sebastian Sardiña: Qualitative Approximate Behavior Composition. JELIA 2012: 450-462
Giuseppe De Giacomo, Fabio Patrizi, Sebastian Sardiña: Agent programming via planning programs. AAMAS 2010: 491-498
Overview of tutorial: a compact summary of the tutorial.
Obs: The set of slides to be used in the actual tutorial will be different and more comprehensive. Still this set of slides should provide a good idea of the topics to be covered.
Full slides for the tutorial can be downloaded below.