scholarly journals Stochastic Market Games

2021 ◽  
Author(s):  
Kyrill Schmid ◽  
Lenz Belzner ◽  
Robert Müller ◽  
Johannes Tochtermann ◽  
Claudia Linnhoff-Popien
Keyword(s):  
Real World ◽  
Autonomous Driving ◽  
Independent Learning ◽  
Market Forces ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Trading Activities ◽  
Conflicting Goals ◽  
Stochastic Market

Some of the most relevant future applications of multi-agent systems like autonomous driving or factories as a service display mixed-motive scenarios, where agents might have conflicting goals. In these settings agents are likely to learn undesirable outcomes in terms of cooperation under independent learning, such as overly greedy behavior. Motivated from real world societies, in this work we propose to utilize market forces to provide incentives for agents to become cooperative. As demonstrated in an iterated version of the Prisoner's Dilemma, the proposed market formulation can change the dynamics of the game to consistently learn cooperative policies. Further we evaluate our approach in spatially and temporally extended settings for varying numbers of agents. We empirically find that the presence of markets can improve both the overall result and agent individual returns via their trading activities.

scholarly journals Multi-agent systems for the real world

2010 ◽  
Author(s):  
Rajiv T. Maheswaran ◽  
Craig M. Rogers ◽  
Romeo Sanchez ◽  
Pedro Szekely ◽  
Robert Neches
Keyword(s):  
Real World ◽  
Multi Agent Systems ◽  
The Real ◽  
Agent Systems ◽  
Multi Agent

scholarly journals Agent organisations: from independent agents to virtual organisations and societies of agents

2020 ◽  
Vol 9 (4) ◽  
pp. 55-70
Author(s):  
Jose Alberto Maestro-Prieto ◽  
Sara Rodríguez ◽  
Roberto Casado ◽  
Juan Manuel Corchado
Keyword(s):  
Real World ◽  
Virtual Organisations ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
Conflicting Objectives ◽  
Real World Applications ◽  
Multi Agent ◽  
The Way

Real world applications using agent-based solutions can include many agents that needs communicate and interact each other in order to meet their objectives. In open multi-agent systems, the problems may include the organisation of a large number of agents that may be heterogeneous, of unpredictable provenance and where competitive behaviours or conflicting objectives may occur. An overview of the alternatives for dealing with these problems is presented, highlighting the way they try to solve or mitigate these problems.

Swarm and Multi-agent Time-based A* Path Planning for Lighter-Than-Air Systems

2020 ◽  
Vol 08 (03) ◽  
pp. 253-260
Author(s):  
Jason Gibson ◽  
Tristan Schuler ◽  
Loy McGuire ◽  
Daniel M. Lofaro ◽  
Donald Sofge
Keyword(s):  
Path Planning ◽  
Dynamic Simulation ◽  
Real World ◽  
Simulation Environment ◽  
Multi Agent Systems ◽  
Time Step ◽  
External Disturbances ◽  
Agent Systems ◽  
Multi Agent ◽  
Velocity Information

This work develops and implements a multi-agent time-based path-planning method using A*. The purpose of this work is to create methods in which multi-agent systems can coordinate actions and complete them at the same time. We utilized A* with constraints defined by a dynamic model of each agent. The model for each agent is updated during each time step and the resulting control is determined. This results in a translational path that each of the agents is physically capable of completing in synchrony. The resulting path is given to the agents as a sequence of waypoints. Periodic updates of the path are calculated, utilizing real-world position and velocity information, as the agents complete the task to account for external disturbances. Our methodology is tested in a dynamic simulation environment as well as on real-world lighter-than-air robotic agents.

A FORMAL HOLONIC FRAMEWORK WITH PROVED SELF-ORGANIZING CAPABILITIES

2007 ◽  
Vol 16 (01) ◽  
pp. 7-25 ◽  
Author(s):  
SEBASTIAN RODRIGUEZ ◽  
VINCENT HILAIRE ◽  
PABLO GRUER ◽  
ABDER KOUKAM
Keyword(s):  
Real World ◽  
Organizational Structures ◽  
The Self ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Real World Problem ◽  
Multi Agent ◽  
Self Similar ◽  
Systems Architectures ◽  
Self Organizing

Numerous works aim to design agents and multi-agent systems architectures in order to enable cooperation and coordination between agents. Most of them use organizational structures or societies metaphor to define the MAS architecture. It seems improbable that a rigid unscalable organization could handle a real world problem, so it is interesting to provide agents with abilities to self-organize according to problem's objectives and environment dynamics. We have chosen the holonic paradigm to provide these abilities to agents. Holons are recursive self-similar entities which are organized in an emergent society — an holarchy. The aim of this paper is to present a formally specified framework for holonic MAS which allows agents to self-organize. The framework is illustrated by an example drawn from a real world problem. Some pertinent properties concerning the self-organizing capabilities of this framework are then proved.

scholarly journals Real-time multi-agent systems: rationality, formal model, and empirical results

2021 ◽  
Vol 35 (1) ◽  
Author(s):  
Davide Calvaresi ◽  
Yashin Dicente Cid ◽  
Mauro Marinoni ◽  
Aldo Franco Dragoni ◽  
Amro Najjar ◽  
...  
Keyword(s):  
Real Time ◽  
Real World ◽  
Intelligent Systems ◽  
Formal Model ◽  
General Purpose ◽  
Timing Constraints ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
The Road ◽  
Multi Agent

AbstractSince its dawn as a discipline, Artificial Intelligence (AI) has focused on mimicking the human mental processes. As AI applications matured, the interest for employing them into real-world complex systems (i.e., coupling AI with Cyber-Physical Systems—CPS) kept increasing. In the last decades, the multi-agent systems (MAS) paradigm has been among the most relevant approaches fostering the development of intelligent systems. In numerous scenarios, MAS boosted distributed autonomous reasoning and behaviors. However, many real-world applications (e.g., CPS) demand the respect of strict timing constraints. Unfortunately, current AI/MAS theories and applications only reason “about time” and are incapable of acting “in time” guaranteeing any timing predictability. This paper analyzes the MAS compliance with strict timing constraints (real-time compliance)—crucial for safety-critical applications such as healthcare, industry 4.0, and automotive. Moreover, it elicits the main reasons for the lack of real-time satisfiability in MAS (originated from current theories, standards, and implementations). In particular, traditional internal agent schedulers (general-purpose-like), communication middlewares, and negotiation protocols have been identified as co-factors inhibiting real-time compliance. To pave the road towards reliable and predictable MAS, this paper postulates a formal definition and mathematical model of real-time multi-agent systems (RT-MAS). Furthermore, this paper presents the results obtained by testing the dynamics characterizing the RT-MAS model within the simulator MAXIM-GPRT. Thus, it has been possible to analyze the deadline miss ratio between the algorithms employed in the most popular frameworks and the proposed ones. Finally, discussing the obtained results, the ongoing and future steps are outlined.

Mechanisms to Restrict Exploitation and Improve Societal Performance in Multi-Agent Systems

2011 ◽  
pp. 182-194
Author(s):  
Sharmila Savarimuthu ◽  
Martin Purvis ◽  
Maryam Purvis ◽  
Mariusz Nowostawski
Keyword(s):  
Resource Utilization ◽  
Real World ◽  
Experimental Results ◽  
Multi Agent Systems ◽  
The Real ◽  
Agent Systems ◽  
Multi Agent ◽  
Overall Performance

Societies are made of different kinds of agents, some cooperative and uncooperative. Uncooperative agents tend to reduce the overall performance of the society, due to exploitation practices. In the real world, it is not possible to decimate all the uncooperative agents; thus the objective of this research is to design and implement mechanisms that will improve the overall benefit of the society without excluding uncooperative agents. The mechanisms that we have designed include referrals and resource restrictions. A referral scheme is used to identify and distinguish noncooperators and cooperators. Resource restriction mechanisms are used to restrict noncooperators from selfish resource utilization. Experimental results are presented describing how these mechanisms operate.

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