Building Redundancy in Multi-Agent Systems Using Probabilistic Selection
نویسندگان
چکیده
In this paper, we examine the effects of probabilistic response on a task allocation problem for a decentralized multi-agent system (MAS) and how such a mechanism may be used to tune the level of redundancy in an MAS. Redundancy refers to a back up pool of agents, beyond the necessary number required to act on a task, that have experience on that task. We present a formal analysis of a response threshold based system in which agents act probabilistically and show that we can estimate the response probability value needed to ensure that a given number of agents will act and that we can estimate the response probability value needed to achieve a given level of redundancy in the system. We perform an empirical study using an agent-based simulation to verify expectations from the formal analysis.
منابع مشابه
Load-Frequency Control: a GA based Bayesian Networks Multi-agent System
Bayesian Networks (BN) provides a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of load-frequency control (LFC). In practice, LFC systems use proportional-integral controllers. However since these controllers are designed using a linear model, the nonlinearities...
متن کاملRedundancy Allocation Combined with Supplier Selection for Design of Series-parallel Systems
In this paper a redundancy allocation problem is studied where for the first time the supplier selection is taken into consideration and redundant components are provided from appropriate suppliers with the most suitable offers such as discount on buying price of components, warranty length for components, things like that, so that the system reliability, profit and the warranty length proposed...
متن کاملSolving a Redundancy Allocation Problem by a Hybrid Multi-objective Imperialist Competitive Algorithm
A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective functi...
متن کاملDiscrimination of Power Quality Distorted Signals Based on Time-frequency Analysis and Probabilistic Neural Network
Recognition and classification of Power Quality Distorted Signals (PQDSs) in power systems is an essential duty. One of the noteworthy issues in Power Quality Analysis (PQA) is identification of distorted signals using an efficient scheme. This paper recommends a Time–Frequency Analysis (TFA), for extracting features, so-called "hybrid approach", using incorporation of Multi Resolution Analysis...
متن کاملConflict Resolution in Probabilistic Multi-Agent Systems
Knowledge representation in the Multi-agent systems (MAS) can be characterized by Probabilistic Network. Coordination among probabilistic agents can be achieved on account of their common knowledge, while agent can obtain his own knowledge locally and variously. To construct the common knowledge for the MAS, the conflict among local knowledge of all agents has to be identified and resolved. We ...
متن کامل