Learning to Respond: The Use of Heuristics in Dynamic Games

While many learning models have been proposed in the game theoretic literature to track individuals’ behavior, surprisingly little research has focused on how well these models describe human adaptation in changing dynamic environments. Analysis of human behavior demonstrates that people are often remarkably responsive to changes in their environment, on time scales ranging from millennia (evolution) to milliseconds (reflex). The goal of this paper is to evaluate several prominent learning models in light of a laboratory experiment on responsiveness in a lowinformation dynamic game subject to changes in its underlying structure. While history-dependent reinforcement learning models track convergence of play well in repeated games, it is shown that they are ill suited to these environments, in which sastisficing models accurately predict behavior. A further objective is to determine which heuristics, or “rules of thumb,” when incorporated into learning models, are responsible for accurately capturing responsiveness. Reference points and a particular type of experimentation are found to be important in both describing and predicting play.learning, limited information, dynamic games

A Bibliography on Fuzzy Automata, Grammars and Lanuages

This bibliography contains references to papers on fuzzy formal languages, the generation of fuzzy languages by means of fuzzy grammars, the recognition of fuzzy languages by fuzzy automata and machines, as well as some applications of fuzzy set theory to syntactic pattern recognition, linguistics and natural language processing

Liveness of Randomised Parameterised Systems under Arbitrary Schedulers (Technical Report)

We consider the problem of verifying liveness for systems with a finite, but unbounded, number of processes, commonly known as parameterised systems. Typical examples of such systems include distributed protocols (e.g. for the dining philosopher problem). Unlike the case of verifying safety, proving liveness is still considered extremely challenging, especially in the presence of randomness in the system. In this paper we consider liveness under arbitrary (including unfair) schedulers, which is often considered a desirable property in the literature of self-stabilising systems. We introduce an automatic method of proving liveness for randomised parameterised systems under arbitrary schedulers. Viewing liveness as a two-player reachability game (between Scheduler and Process), our method is a CEGAR approach that synthesises a progress relation for Process that can be symbolically represented as a finite-state automaton. The method is incremental and exploits both Angluin-style L*-learning and SAT-solvers. Our experiments show that our algorithm is able to prove liveness automatically for well-known randomised distributed protocols, including Lehmann-Rabin Randomised Dining Philosopher Protocol and randomised self-stabilising protocols (such as the Israeli-Jalfon Protocol). To the best of our knowledge, this is the first fully-automatic method that can prove liveness for randomised protocols.Comment: Full version of CAV'16 pape