Designing games to handle coupled constraints

The central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to a given system level objective. In many systems, such as cooperative robotics or distributed power control, the design of these local control algorithms is further complicated by additional coupled constraints on the agents' actions. There are several approaches in the existing literature for designing such algorithms stemming from classical optimization theory; however, many of these approaches are not suitable for implementation in multiagent systems. This paper seeks to address the design of such algorithms using the field of game theory. Among other things, this design choice requires defining a local utility function for each decision maker in the system. This paper seeks to address the degree to which utility design can be effective for dealing with these coupled constraints. In particular, is it possible to design local agent utility functions such that all pure Nash equilibrium of the unconstrained game (i) optimize the given system level objective and (ii) satisfy the given coupled constraint. This design would greatly simplify the distributed control algorithms by eliminating the need to explicitly consider the constraints. Unfortunately, we illustrate that designing utility functions within the standard game theoretic framework is not suitable for this design objective. However, we demonstrate that by adding an additional state variable in the game environment, i.e., moving towards state based games, we can satisfy these performance criteria by utility design. We focus on the problem of consensus control to illustrate these results

Maximising microprocessor reliability through game theory and heuristics

PhD ThesisEmbedded Systems are becoming ever more pervasive in our society, with most routine daily tasks now involving their use in some form and the market predicted to be worth USD 220 billion, a rise of 300%, by 2018. Consumers expect more functionality with each design iteration, but for no detriment in perceived performance. These devices can range from simple low-cost chips to expensive and complex systems and are a major cost driver in the equipment design phase. For more than 35 years, designers have kept pace with Moore's Law, but as device size approaches the atomic limit, layouts are becoming so complicated that current scheduling techniques are also reaching their limit, meaning that more resource must be reserved to manage and deliver reliable operation. With the advent of many-core systems and further sources of unpredictability such as changeable power supplies and energy harvesting, this reservation of capability may become so large that systems will not be operating at their peak efficiency. These complex systems can be controlled through many techniques, with jobs scheduled either online prior to execution beginning or online at each time or event change. Increased processing power and job types means that current online scheduling methods that employ exhaustive search techniques will not be suitable to define schedules for such enigmatic task lists and that new techniques using statistic-based methods must be investigated to preserve Quality of Service. A new paradigm of scheduling through complex heuristics is one way to administer these next levels of processor effectively and allow the use of more simple devices in complex systems; thus reducing unit cost while retaining reliability a key goal identified by the International Technology Roadmap for Semi-conductors for Embedded Systems in Critical Environments. These changes would be beneficial in terms of cost reduction and system exibility within the next generation of device. This thesis investigates the use of heuristics and statistical methods in the operation of real-time systems, with the feasibility of Game Theory and Statistical Process Control for the successful supervision of high-load and critical jobs investigated. Heuristics are identified as an effective method of controlling complex real-time issues, with two-person non-cooperative games delivering Nash-optimal solutions where these exist. The simplified algorithms for creating and solving Game Theory events allow for its use within small embedded RISC devices and an increase in reliability for systems operating at the apex of their limits. Within this Thesis, Heuristic and Game Theoretic algorithms for a variety of real-time scenarios are postulated, investigated, refined and tested against existing schedule types; initially through MATLAB simulation before testing on an ARM Cortex M3 architecture functioning as a simplified automotive Electronic Control Unit.Doctoral Teaching Account from the EPSRC

Applications of Game Theory to Multi-Agent Coordination Problems in Communication Networks

Recent years there has been a growing interest in the study of distributed control mechanisms for use in communication networks. A fundamental assumption in these models is that the participants in the network are willing to cooperate with the system. However, there are many instances where the incentives to cooperate is missing. Then, the agents may seek to achieve their own private interests by behaving strategically. Often, such selfish choices lead to inefficient equilibrium state of the system, commonly known as the tragedy of commons in Economics terminology. Now, one may ask the following question: how can the system be led to the socially optimal state in spite of selfish behaviors of its participants? The traditional control design framework fails to provide an answer as it does not take into account of selfish and strategic behavior of the agents. The use of game theoretical methods to achieve coordination in such network systems is appealing, as it naturally captures the idea of rational agents taking locally optimal decisions. In this thesis, we explore several instances of coordination problems in communication networks that can be analyzed using game theoretical methods. We study one coordination problem each, from each layer of TCP/IP reference model - the network model used in the current Internet architecture. First, we consider societal agents taking decisions on whether to obtain content legally or illegally, and tie their behavior to questions of performance of content distribution networks. We show that revenue sharing with peers promote performance and revenue extraction from content distribution networks. Next, we consider a transport layer problem where applications compete against each other to meet their performance objectives by selfishly picking congestion controllers. We establish that tolling schemes that incentivize applications to choose one of several different virtual networks catering to particular needs yields higher system value. Hence, we propose the adoption of such virtual networks. We address a network layer question in third problem. How do the sources in a wireless network split their traffic over the available set of paths to attain the lowest possible number of transmissions per unit time? We develop a two level distributed controller that attains the optimal traffic split. Finally, we study mobile applications competing for channel access in a cellular network. We show that the mechanism where base station conducting sequence of second price auctions and providing channel access to the winner achieves the benefits of the state of art solution, Largest Queue First policy

Overcoming Limitations of Game-Theoretic Distributed Control

Abstract—Recently, game theory has been proposed as a tool for cooperative control. Specifically, the interactions of a multiagent distributed system are modeled as a non-cooperative game where agents are self-interested. In this work, we prove that this approach of non-cooperative control has limitations with respect to engineering multi-agent systems. In particular, we prove that it is not possible to design budget balanced agent utilities that also guarantee that the optimal control is a Nash equilibrium. However, it is important to realize that game-theoretic designs are not restricted to the framework of non-cooperative games. In particular, we demonstrate that these limitations can be overcome by conditioning each player’s utility on additional information, i.e., a state. This utility design fits into the framework of a particular form of stochastic games termed state-based games and is applicable in many application domains. I