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Research output per year
Julian Gutierrez, Paul Harrenstein, Michael Wooldridge
Research output: Contribution to journal › Article › Research › peer-review
Model checking is the best-known and most successful approach to formally verifying that systems satisfy specifications, expressed as temporal logic formulae. In this article, we develop the theory of equilibrium checking, a related but distinct problem. Equilibrium checking is relevant for multi-agent systems in which system components (agents) are assumed to be acting rationally in pursuit of delegated goals, and is concerned with understanding what temporal properties hold of such systems under the assumption that agents select strategies in equilibrium. The formal framework we use to study this problem assumes agents are modelled using REACTIVE MODULES, a system modelling language that is used in a range of practical model checking systems. Each agent (or player) in a REACTIVE MODULES game is specified as a nondeterministic guarded command program, and each player's goal is specified with a temporal logic formula that the player desires to see satisfied. A strategy for a player in a REACTIVE MODULES game defines how that player selects enabled guarded commands for execution over successive rounds of the game. For this general setting, we investigate games in which players have goals specified in Linear Temporal Logic (in which case it is assumed that players choose deterministic strategies) and in Computation Tree Logic (in which case players select nondeterministic strategies). For each of these cases, after formally defining the game setting, we characterise the complexity of a range of problems relating to Nash equilibria (e.g., the computation or the verification of existence of a Nash equilibrium or checking whether a given temporal formula is satisfied on some Nash equilibrium). We then go on to show how the model we present can be used to encode, for example, games in which the choices available to players are specified using STRIPS planning operators.
Original language | English |
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Pages (from-to) | 123-157 |
Number of pages | 35 |
Journal | Artificial Intelligence |
Volume | 248 |
DOIs | |
Publication status | Published - Jul 2017 |
Externally published | Yes |
Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review