Information-Based Interaction-Oriented Programming, specifically as epitomized by the Blindingly Simple Protocol Language (BSPL), is a promising new approach for declaratively expressing multiagent protocols. BSPL eschews traditional control flow ...

We consider models of multi-player games where abilities of players and coalitions are defined in terms of sets of outcomes which they can effectively enforce. We extend the well studied state effectivity models of one-step games in two different ways. ...

The last decade has been witness to a rapid growth of interest in logics intended to support reasoning about the interactions between knowledge and action. Typically, logics combining dynamic and epistemic components contain ontic actions (which change ...

Coalition logic is currently one of the most popular logics for multi-agent systems. While logics combining coalitional and epistemic operators have received considerable attention, completeness results for epistemic extensions of coalition logic have ...

Autonomous agents typically have several goals they are pursuing simultaneously. Even if the goals themselves are not necessarily inconsistent, choices made about how to pursue each of these goals may well result in a set of intentions which are ...

We introduce Comma, a methodology for developing cross-organizational business models. Comma gives prime position to patterns of business relationships understood in terms of commitments. In this manner, it contrasts with traditional operational ...

A great number of methodologies has been already introduced in the agent-oriented software engineering field. Recently many of the authors of these methodologies also worked on their fragmentation thus obtaining portions (often called method or process ...

In Belief Desire Intention (BDI) agent systems it is usual for goals to have a number of plans that are possible ways of achieving the goal, applicable in different situations, usually captured by a context condition. In Agent Oriented Software ...

Policy iteration algorithms for partially observable Markov decision processes (POMDP) offer the benefits of quick convergence and the ability to operate directly on the solution, which usually takes the form of a finite state controller. However, the ...

Interactive multiagent decision making often requires to predict actions of other agents by solving their behavioral models from the perspective of the modeling agent. Unfortunately, the general space of models in the absence of constraining assumptions ...

We consider the problem of automated planning and control for an execution agent operating in environments that are partially-observable with deterministic exogenous events. We describe a new formalism and a new algorithm, DiscoverHistory, that enables ...

Multiagent planning under uncertainty has seen important progress in recent years. Two techniques, in particular, have substantially advanced efficiency and scalability of planning. Multiagent heuristic search gains traction by pruning large portions of ...

In many multiagent domains, no single observation event is sufficient to determine that the behavior of individuals is suspicious. Instead, suspiciousness must be inferred from a combination of multiple events, where events refer to the individual's ...

This article presents a population-based cognitive hierarchy model that can be used to estimate the reasoning depth and sophistication of a collection of opponents' strategies from observed behavior in repeated games. This framework provides a compact ...

Boolean games are a compact and expressive class of games, based on propositional logic. However, Boolean games are computationally complex: checking for the existence of pure Nash equilibria in Boolean games is Σ^p/₂-complete, and it is co-NP-complete ...

Studies in experimental economics have consistently demonstrated that Nash equilibrium is a poor description of human players' behavior in unrepeated normal-form games. Behavioral game theory offers alternative models that more accurately describe human ...

We study the problem of optimal resource allocation for packet selection and inspection to detect potential threats in large computer networks with multiple computers of differing importance. An attacker tries to harm these targets by sending malicious ...

We consider multi-player games, and the guarantees that a master player that plays on behalf of a set of players can offer them, without making any assumptions on the rationality of the other players. Our model consists of an (n + 1)-player game, with m ...

Moving assets through a transportation network is a crucial challenge in hostile environments such as future battlefields where malicious adversaries have strong incentives to attack vulnerable patrols and supply convoys. Intelligent agents must balance ...

There has been significant recent interest in computing effective strategies for playing large imperfect-information games. Much prior work involves computing an approximate equilibrium strategy in a smaller abstract game, then playing this strategy in ...