On an Evolutionary Approach to Language

Author(s):  
Goran Trajkovski

The focus of this chapter is the explanation of a method for allowing languages to emerge within a multi-agent system. The need for such a method tends to be in larger multi-agent systems that focus either on large domains or span across multiple domains. This method can also be adapted for interfacing multi-agent systems with humans through natural languages. Also addressed in this chapter are the necessary requirements for a multi-agent system to utilize an evolving communication system. A specification of an evolving vocabulary is presented along with an explanation of results from an experiment that contains an implementation of these specifications.

Author(s):  
Robert E. Smith ◽  
Claudio Bonacina

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.


2016 ◽  
Vol 40 (2) ◽  
pp. 504-513 ◽  
Author(s):  
Lei Chen ◽  
Kaiyu Qin ◽  
Jiangping Hu

In this paper, we investigate a tracking control problem for second-order multi-agent systems. Here, the leader is self-active and cannot be completely measured by all the followers. The interaction network associated with the leader–follower multi-agent system is described by a jointly connected topology, where the topology switches over time and is not strongly connected during each time subinterval. We consider a consensus control of the multi-agent system with or without time delay and propose two categories of neighbour-based control rules for every agent to track the leader, then provide sufficient conditions to ensure that all agents follow the leader, and meanwhile, the tracking errors can be estimated. Finally, some simulation results are presented to demonstrate our theoretical results.


1996 ◽  
Vol 4 ◽  
pp. 477-507 ◽  
Author(s):  
R. I. Brafman ◽  
M. Tennenholtz

Motivated by the control theoretic distinction between controllable and uncontrollable events, we distinguish between two types of agents within a multi-agent system: controllable agents, which are directly controlled by the system's designer, and uncontrollable agents, which are not under the designer's direct control. We refer to such systems as partially controlled multi-agent systems, and we investigate how one might influence the behavior of the uncontrolled agents through appropriate design of the controlled agents. In particular, we wish to understand which problems are naturally described in these terms, what methods can be applied to influence the uncontrollable agents, the effectiveness of such methods, and whether similar methods work across different domains. Using a game-theoretic framework, this paper studies the design of partially controlled multi-agent systems in two contexts: in one context, the uncontrollable agents are expected utility maximizers, while in the other they are reinforcement learners. We suggest different techniques for controlling agents' behavior in each domain, assess their success, and examine their relationship.


2017 ◽  
Vol 58 ◽  
Author(s):  
Jaroslav Meleško ◽  
Eugenijus Kurilovas ◽  
Irina Krikun

The paper aims to analyse application trends of intelligent multi-agent systems to personalise learning. First of all, systematic literature review was performed. Based on the systematic review analysis, the main trends on applying multi-agent systems to personalise learning were identified. Second, main requirements and components for an educational multi-agent system were formulated. Third, based on these components a model of intelligent personalized system is proposed. The system employs five intelligent agents: (1) learning styles identification software agent, (2) learner profile creation software agent, (3) pedagogical suitability software agent, (4) optimal learning units/scenarios creation software agent, and (5) learning analytics/educational data mining software agent.


Author(s):  
Robert E. Smith ◽  
Claudia Bonacina

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.


2017 ◽  
pp. 083-096
Author(s):  
A.L. Yalovets ◽  

The features of the design, development and functioning of the multi-agent system Navigation are investigated. System architecture and substantiate the choice of language implementation of the system are provided. The functionality of the subsystems of multi-agent systems Navigation is analyzed in detail. The results of multi-agent modelling of pursuit/escape processes by means of the multi-agent system in different modes of its functioning are compared on meaningful example.


Author(s):  
MIHAELA ULIERU ◽  
RAINER UNLAND

In today's world, it is of utterly importance for enterprises to react in a timely and flexible way to upcoming complex market demands. One solution is given by the concept of virtual enterprise and enterprise alliances, respectively. In order to function efficiently and flexibly such enterprises need to be deeply integrated. Based on previous work combining the concepts of virtual enterprises, holonic organizations and multi-agent systems to support such deep integration, the paper discusses in detail how well-suiting partners and contributors for a given (bunch of) task(s) can be found using today's state-of-the-art technologies. Mapping an enterprise alliance onto a multi-agent system is enabled by a methodology equipping each agent with the ability to deal and consider its own goals (goals of the unit it represents) as well as the goals of the unit in which it is integrated (the higher level unit).


2021 ◽  
Vol 70 ◽  
pp. 389-407
Author(s):  
Guangqiang Xie ◽  
Junyu Chen ◽  
Yang Li

As an important field of Distributed artificial intelligence (DAI), multi-agent systems (MASs) have attracted the attention of extensive research scholars. Consensus as the most important issue in MAS, much progress has been made in studying the consensus control of MAS, but there are some problems remained largely unaddressed which cause the MAS to lose some useful network structure information. First, multi-agent consensus protocol usually proceeds over the low-order structure by only considering the direct edges between agents, but ignores the higher-order structure of the whole topology network. Second, the existing work assumes all the edges in a topology network have the same weight without exploring the potential diversity of the connections. In this way, multi-agent systems fail to enforce consensus, resulting in fragmentation into multiple clusters. To address the above issues, this paper proposes a Motif-aware Weighted Multi-agent System (MWMS) method for consensus control. We focus more on triangle motif in the network, but it can be extended to other kinds of motifs as well. First, a novel weighted network is used which is the combination of the edge-based lower-order structure and the motif-based higher-order structure, i.e., hybrid-order structure. Subsequently, by simultaneously considering the quantity and the quality of the connections in the network, a novel consensus framework for MAS is designed to update agents. Then, two baseline consensus algorithms are used in MWMS. In our experiments, we use ten topologies of different shapes, densities and ranges to comprehensively analyze the performance of our proposed algorithms. The simulation results show that the hybrid higher-order network can effectively enhance the consensus of the multi-agent system in different network topologies.


2013 ◽  
Vol 5 (2) ◽  
pp. 85-93 ◽  
Author(s):  
Mohamed Osama Khozium

A software agent should be autonomous, flexible, robust and social. The increasing importance of the Multi-Agent System (MAS) has led to the greater availability of tools designed to facilitate their creation and use. To devise agents is considered a real challenge which faces analysts and designers during development of any multi-agent systems. This paper proposes a methodology to determine, clarify and differentiate among agents during development of multi-agent systems using goals and functionalities grouping approach. A step by step case of study is presented to explain the proposed methodology for the creation of an Online Intelligent System (OIS) for Board of Directors guide using Multi-Agent System to facilitate online communication between the board members and their president to monitor the policies and productivity of the company.


Author(s):  
Panagiotis Kouvaros ◽  
Alessio Lomuscio ◽  
Edoardo Pirovano

We study the problem of determining the robustness of a multi-agent system of unbounded size against specifications expressed in a temporal-epistemic logic. We introduce a procedure to synthesise automatically the maximal ratio of faulty agents that may be present at runtime for a specification to be satisfied in a multi-agent system. We show the procedure to be sound and amenable to symbolic implementation. We present an implementation and report the experimental results obtained by running this on a number of protocols from swarm robotics.


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