Concurrent Stochastic Lossy Channel Games

Concurrent stochastic games are an important formalism for the rational verification of probabilistic multi-agent systems, which involves verifying whether a temporal logic property is satisfied in some or all game-theoretic equilibria of such systems. In this work, we study the rational verification of probabilistic multi-agent systems where agents can cooperate by communicating over unbounded lossy channels. To model such systems, we present concurrent stochastic lossy channel games (CSLCG) and employ an equilibrium concept from cooperative game theory known as the core, which is the most fundamental and widely studied cooperative equilibrium concept. Our main contribution is twofold. First, we show that the rational verification problem is undecidable for systems whose agents have almost-sure LTL objectives. Second, we provide a decidable fragment of such a class of objectives that subsumes almost-sure reachability and safety. Our techniques involve reductions to solving infinite-state zero-sum games with conjunctions of qualitative objectives. To the best of our knowledge, our result represents the first decidability result on the rational verification of stochastic multi-agent systems on infinite arenas.Comment: To appear at CSL 2024. Extended versio

Overdetermined Causation Cases, Contribution and the Shapley Value

The overdetermined causation cases (duplicative causation, concurrent causes, etc.) challenge the consistency and relevance of the but for test in torts. A strict application of the but for criterion to these cases leads to paradoxes and solutions that violate common sense. This explains why a large amount of literature has been developed in philosophy and jurisprudence to provide more accurate causation criteria. This paper adds to this literature by considering over-determination cases from an economic and mathematical point of view. Following Martin van Hees and Matthew Braham in their 2009 article Degrees of Causation, we consider over-determined cases through cooperative game theory and define “overdetermined causation games”. We characterize these games in terms of marginal contribution to the great coalition and we provide a typology of different overdetermined causation cases. Lastly, we apply to these games a traditional sharing rule developed in cooperative game theory, the Shapley value, to assess the “causal” contribution of each tortfeasor

Automated verification of concurrent stochastic games

We present automatic verifcation techniques for concurrent stochastic multi-player games (CSGs) with rewards. To express properties of such models, we adapt the temporal logic rPATL (probabilistic alternating-time temporal logic with rewards), originally introduced for the simpler model of turn-based games, which enables quantitative reasoning about the ability of coalitions of players to achieve goals related to the probability of an event or reward measures. We propose and implement a modelling approach and model checking algorithms for property verifcation and strategy synthesis of CSGs, as an extension of PRISMgames. We evaluate the performance, scalability and applicability of our techniques on case studies from domains such as security, networks and finance, showing that we can analyse systems with probabilistic, cooperative and competitive behaviour between concurrent components, including many scenarios that cannot be analysed with turn-based models

Characterising and Verifying the Core in Concurrent Multi-Player Mean-Payoff Games (Full Version)

Concurrent multi-player mean-payoff games are important models for systems of agents with individual, non-dichotomous preferences. Whilst these games have been extensively studied in terms of their equilibria in non-cooperative settings, this paper explores an alternative solution concept: the core from cooperative game theory. This concept is particularly relevant for cooperative AI systems, as it enables the modelling of cooperation among agents, even when their goals are not fully aligned. Our contribution is twofold. First, we provide a characterisation of the core using discrete geometry techniques and establish a necessary and sufficient condition for its non-emptiness. We then use the characterisation to prove the existence of polynomial witnesses in the core. Second, we use the existence of such witnesses to solve key decision problems in rational verification and provide tight complexity bounds for the problem of checking whether some/every equilibrium in a game satisfies a given LTL or GR(1) specification. Our approach is general and can be adapted to handle other specifications expressed in various fragments of LTL without incurring additional computational costs.Comment: This is the full version of the paper with the same title that appears in the CSL'24 proceeding

Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence

Learning agents that are not only capable of taking tests, but also innovating is becoming a hot topic in AI. One of the most promising paths towards this vision is multi-agent learning, where agents act as the environment for each other, and improving each agent means proposing new problems for others. However, existing evaluation platforms are either not compatible with multi-agent settings, or limited to a specific game. That is, there is not yet a general evaluation platform for research on multi-agent intelligence. To this end, we introduce Arena, a general evaluation platform for multi-agent intelligence with 35 games of diverse logics and representations. Furthermore, multi-agent intelligence is still at the stage where many problems remain unexplored. Therefore, we provide a building toolkit for researchers to easily invent and build novel multi-agent problems from the provided game set based on a GUI-configurable social tree and five basic multi-agent reward schemes. Finally, we provide Python implementations of five state-of-the-art deep multi-agent reinforcement learning baselines. Along with the baseline implementations, we release a set of 100 best agents/teams that we can train with different training schemes for each game, as the base for evaluating agents with population performance. As such, the research community can perform comparisons under a stable and uniform standard. All the implementations and accompanied tutorials have been open-sourced for the community at https://sites.google.com/view/arena-unity/

Reactive concurrent programming revisited

In this note we revisit the so-called reactive programming style, which evolves from the synchronous programming model of the Esterel language by weakening the assumption that the absence of an event can be detected instantaneously. We review some research directions that have been explored since the emergence of the reactive model ten years ago. We shall also outline some questions that remain to be investigated