Modular Heterogeneous Multi-Agent Control Framework with Integrated Payloads

Small unmanned aircraft are being used in an increasing number of applications ranging from emergency response to parcel delivery. Many of these applications are benefited when employed as a multiple-vehicle operation. Such operations often require tight cooperation between heterogeneous vehicles and often depend on integration with sensors and payloads. Multi-agent control algorithms can be implemented to control such systems but often require the development of an underlying vehicle communications framework in addition to a sensors and payloads communications framework. This thesis presents a single unified modular framework, named Clark, and supports heterogeneous multi-agent control and sensor/payload integration. Clark provides a wireless network between agents without relying on pre-existing communications infrastructure, and provides software interfaces for connecting to a variety of payloads. This thesis first reviews small unmanned aircraft systems (SUAS), multi-agent control, multi-agent control testbeds, and wireless networking technologies used on SUAS. Systems engineering is then employed to develop an Identified Need, Concept of Operations (ConOps), and requirements. All Defined, Derived, and Design Requirements are explained and justified. Some requirements are highlighted to demonstrate key features of the Clark framework. The software architecture is explained in detail in a top-down approach. Hardware is selected for prototyping and shown to meet the requirements. Bench tests, ground tests, and flight tests are conducted to verify the framework’s ability to communicate between agents and affect control. Ground testing includes a multi-agent cooperative mission while flight testing features two and three agent missions. Test results are presented and demonstrate the candidacy of Clark as a modular heterogeneous multi-agent control framework with integrated payloads

Agent Based Software Testing for Multi Agent Systems

Software testing starts with verification and validation and fulfills the requirement of the customer. Testing can be done by automation tool like Win runner, QTP or manually. If we talk about manual testing it takes lot of time and manpower also so nowadays we are using automation software. When we talk about automation testing so the cost of such kind of testing is very high so each company cannot afford. In this paper we are presenting agent based testing which is helpful for both kind of testing. Multi-Agent Systems (MAS) are characterized by autonomous and collaborative behaviors [1, 2]. Developing such systems is a complex process. As a result, a methodology for developing MAS is highly necessary. In this paper, a methodology using roles and ontology for such a purpose is presented [2]. The functionality of roles is estimated in the various phases of the MAS development. It is based on an emphasis on the properties and behaviors associated with each agent in MAS

Behaviour Driven Development for Multi-Agent Systems

This paper presents a testing methodology to apply Behaviour Driven Development (BDD) techniques while developing Multi-Agent Systems (MAS), so called BEhavioural Agent Simple Testing (BEAST) methodology. It is supported by the developed open source framework (BEAST Tool) which automatically generates test cases skeletons from BDD scenarios specifications. The developed framework allows testing MASs based on JADE or JADEX platforms and offers a set of configurable Mock Agents which allow the execution of tests while the system is under development. BEAST tool has been validated in the development of a MAS for fault diagnosis in FTTH (Fiber To The Home) networks

Multi‐agent technologies in economics

This paper summarizes some of the trends in the use of multi‐agent technologies in economics. Multiple agent systems, fuzzy sets and neural networks are critical tools used to investigate the emerging economics research agenda related to data mining, dynamic markets stock selection and bank stress testing. This paper reviews the contributions of four such examples.Ministerio de Economía y Competitividad TIN2015‐65515‐C4‐3‐

A Multi-Agent Framework for Testing Distributed Systems

Software testing is a very expensive and time consuming process. It can account for up to 50% of the total cost of the software development. Distributed systems make software testing a daunting task. The research described in this paper investigates a novel multi-agent framework for testing 3-tier distributed systems. This paper describes the framework architecture as well as the communication mechanism among agents in the architecture. Web-based application is examined as a case study to validate the proposed framework. The framework is considered as a step forward to automate testing for distributed systems in order to enhance their reliability within an acceptable range of cost and time

Decision Support for Negotiations among Microgrids Using a Multiagent Architecture

[EN] This paper presents a decision support model for negotiation portfolio optimization considering the participation of players in local markets (at the microgrid level) and in external markets, namely in regional markets, wholesale negotiations and negotiations of bilateral agreements. A local internal market model for microgrids is defined, and the connection between interconnected microgrids is based on nodal pricing to enable negotiations between nearby microgrids. The market environment considering the local market setting and the interaction between integrated microgrids is modeled using a multi-agent approach. Several multi-agent systems are used to model the electricity market environment, the interaction between small players at a microgrid scale, and to accommodate the decision support features. The integration of the proposed models in this multi-agent society and interaction between these distinct specific multi-agent systems enables modeling the system as a whole and thus testing and validating the impact of the method in the outcomes of the involved players. Results show that considering the several negotiation opportunities as complementary and making use of the most appropriate markets depending on the expected prices at each moment allows players to achieve more profitable results

Incorporating Inertia Into Multi-Agent Systems

We consider a model that demonstrates the crucial role of inertia and stickiness in multi-agent systems, based on the Minority Game (MG). The inertia of an agent is introduced into the game model by allowing agents to apply hypothesis testing when choosing their best strategies, thereby reducing their reactivity towards changes in the environment. We find by extensive numerical simulations that our game shows a remarkable improvement of global cooperation throughout the whole phase space. In other words, the maladaptation behavior due to over-reaction of agents is removed. These agents are also shown to be advantageous over the standard ones, which are sometimes too sensitive to attain a fair success rate. We also calculate analytically the minimum amount of inertia needed to achieve the above improvement. Our calculation is consistent with the numerical simulation results. Finally, we review some related works in the field that show similar behaviors and compare them to our work.Comment: extensively revised, 8 pages, 10 figures in revtex