Abstract
Distributed constraint satisfaction problems (DisCSPs) are among the widely endeavored problems using agent-based simulation. Fernandez et al. formulated sensor and mobile tracking problem as a DisCSP, known as SensorDCSP In this paper, we adopt a customized ERE (environment, reactive rules and entities) algorithm for the SensorDCSP, which is otherwise proven as a computationally intractable problem. An amalgamation of the autonomy-oriented computing (AOC)-based algorithm (ERE) and genetic algorithm (GA) provides an early solution of the modeled DisCSP. Incorporation of GA into ERE facilitates auto-tuning of the simulation parameters, thereby leading to an early solution of constraint satisfaction. This study further contributes towards a model, built up in the NetLogo simulation environment, to infer the efficacy of the proposed approach.
Highlights
Agent-based simulations are widely employed to address computationally hard problems in a distributed context
The identification of the set of variables and imposed constraints is imperative to represent the problem as a constraint satisfaction problem (CSP) (Definition 1)
We developed a model in NetLogo [28] to simulate SensorDSCP using the proposed approach
Summary
Agent-based simulations are widely employed to address computationally hard problems in a distributed context. These problems are either innately distributed in nature [1] or formulated as an instance of distributed constraint satisfaction problems (DisCSPs). Computers 2015, 4 have been proposed to model diversified computationally intractable problems in the context of DisCSP. The identification of the set of variables and imposed constraints is imperative to represent the problem as a constraint satisfaction problem (CSP) (Definition 1). Each constraint pertains to some subset of variables and limits the permitted combinations of variable values in the subset. Solving a CSP requires identifying one such assignment of variables that meet all constraints. The aim is to obtain all sets of such assignments. Finding the number of all possible solutions to a given
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
