Titlebook: Safety and Security in Multiagent Systems; Research Results fro Mike Barley,Haralambos Mouratidis,Fabio Massacci Conference proceedings 200

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杂役

Safe Stochastic Planning: Planning to Avoid Fatal Statesal policies or plans. One area that is often missing from discussions of planning under stochastic environment is how MDPs handle safety constraints expressed as probability of reaching threat states. We introduce a method for finding a value optimal policy satisfying the safety constraint, and repo

实现

Building Coordinated Real-Time Control PlansIn particular, we are developing methods for teams of CIRCA agents to build coordinated plans that include explicit runtime communications to support distributed real-time reactivity to the environment. These teams can build plans in which different agents use their unique capabilities to guarantee

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A Framework for Goal-Based Semantic Compensation in Agent Systems on the concept of semantic compensation: “cleaning up” failed or canceled tasks can help agents behave more robustly and predictably at both an individual and system level. Our approach is goal-based, both with respect to defining failure-handling knowledge, and in specifying a failure-handling mod

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BANAL

Uncertain Agent Verification through Probabilistic Model-Checkingcase (agents’) decision-making becomes probabilistic too. In this work we consider a probabilistic variant of a well-known (two-players) Negotiation game and we show, first, how it can be encoded into a Markovian model, and then how a probabilistic model-checker such as PRISM can be used as a tool f

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