Pretty Good Strategies and Where to Find Them

Synthesis of bulletproof strategies in imperfect information scenarios is a notoriously hard problem. In this paper, we suggest that it is sometimes a viable alternative to aim at "reasonably good" strategies instead. This makes sense not only when an ideal strategy cannot be found due to the complexity of the problem, but also when no winning strategy exists at all. We propose an algorithm for synthesis of such "pretty good" strategies. The idea is to first generate a surely winning strategy with perfect information, and then iteratively improve it with respect to two criteria of dominance: one based on the amount of conflicting decisions in the strategy, and the other related to the tightness of its outcome set. We focus on reachability goals and evaluate the algorithm experimentally with very promising results

Towards Assume-Guarantee Verification of Strategic Ability

Formal verification of strategic abilities is a hard problem. We propose to use the methodology of assume-guarantee reasoning in order to facilitate model checking of alternating-time temporal logic with imperfect information and imperfect recall

Towards Modelling and Verification of Social Explainable AI

Social Explainable AI (SAI) is a new direction in artificial intelligence that emphasises decentralisation, transparency, social context, and focus on the human users. SAI research is still at an early stage. Consequently, it concentrates on delivering the intended functionalities, but largely ignores the possibility of unwelcome behaviours due to malicious or erroneous activity. We propose that, in order to capture the breadth of relevant aspects, one can use models and logics of strategic ability, that have been developed in multi-agent systems. Using the STV model checker, we take the first step towards the formal modelling and verification of SAI environments, in particular of their resistance to various types of attacks by compromised AI modules

Assume-Guarantee Verification of Strategic Ability

Model checking of strategic abilities is a notoriously hard problem, even more so in the realistic case of agents with imperfect information. Assume-guarantee reasoning can be of great help here, providing a way to decompose the complex problem into a small set of exponentially easier subproblems. In this paper, we propose two schemes for assume-guarantee verification of alternating-time temporal logic with imperfect information. We prove the soundness of both schemes, and discuss their completeness. We illustrate the method by examples based on known benchmarks, and show experimental results that demonstrate the practical benefits of the approach

STV+Reductions: Towards Practical Verification of Strategic Ability Using Model Reductions

We present a substantially expanded version of our tool STV for strategy synthesis and verification of strategic abilities. The new version adds user-definable models and support for model reduction through partial order reduction and checking for bisimulation