Goals and Resource Constraints in CARMA

Piho, Paul; Georgoulas, Anastasis; Hillston, Jane

doi:10.1016/j.entcs.2018.03.039

Cited by 2 publications

(1 citation statement)

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“…Firstly, we propose a class of systems arising from collective systems involving broadcast communication. Secondly, we present a process algebra based on the existing language Carma [5] which together with specification of goals from [6] provides a high level framework for formulating policy synthesis problems. Next, we propose an efficient policy synthesis approach, exploiting the structure suggested by the language level description, to find configurations that can satisfy the defined collective goals.…”

Section: Introductionmentioning

confidence: 99%

Policy Synthesis for Collective Dynamics

Piho

Hillston

2018

Quantitative Evaluation of Systems

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In this paper we consider the problem of policy synthesis for systems of large numbers of simple interacting agents where dynamics of the system change through information spread via broadcast communication. By modifying the existing modelling language Carma and giving it a semantics in terms of continuous time Markov decision processes we introduce a natural way of formulating policy synthesis problems for such systems. However, solving policy synthesis problems is difficult since all non-trivial models result in very large state spaces. To combat this we propose an approach exploiting the results on fluid approximations of continuous time Markov chains to obtain estimates of optimal policies.

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Section: Introductionmentioning

confidence: 99%