Mobile agent strategies for the provision of public goods: An experimental study (original) (raw)
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A Software Engineering Approach for Agent-Based Modelling and Simulation of Public Goods Games
In Agent-based Modelling and Simulation (ABMS), a system is modelled as a collection of agents, which are autonomous decision-making units with diverse characteristics. The interaction of the individual behaviours of the agents results in the global behaviour of the system. Because ABMS offers a methodology to create an artificial society in which actors with their behaviour can be designed and results of their interaction can be observed, it has gained attention in social sciences such as Economics, Ecology, Social Psychology, and Sociology. In Economics, ABMS has been used to model many strategic situations. One of the popular strategic situations is the Public Goods Game (PGG). In the PGG, participants secretly choose how many of their private money units to put into a public pot. Social scientists can conduct laboratory experiments of PGGs to study human behaviours in strategic situations. Research findings from these laboratory studies have inspired studies using computational agents and vice versa. However, there is a lack of guidelines regarding the detailed development process and the modelling of agent behaviour for agent-based models of PGGs. We believe that this has contributed to ABMS of PGG not having been used to its full potential. This thesis aims to leverage the potential of ABMS of PGG, focusing on the development methodology of ABMS and the modelling of agent behaviour. We construct a development framework with incorporated software engineering techniques, then tailored it to ABMS of PGG. The framework uses the Unified Modelling Language (UML) as a standard specification language, and includes a simulation development lifecycle, a step-by-step development guideline, and a short guide for modelling agent behaviour with statecharts. It utilizes software engineering methods to provide a structured approach to identify agent interactions, and design simulation architecture and agent behaviour. The framework is named ABOOMS (Agent-Based Object-Oriented Modelling and Simulation). After applying the ABOOMS framework to three case studies, the framework demonstrates flexibility in development with two different modelling principles (Keep-It-Simple-Stupid vs. Keep-It-Descriptive-Stupid), capability in supporting complex psychological mechanisms, and ability to model dynamic behaviours in both discrete and continuous time. Additionally, the thesis developed an agent-based model of a PGG in a continuous-time setting. To the best of our knowledge such agent-based models do not exist. During the development, a new social preference, Generous Conditional Cooperators, was introduced to better explain the behavioural dynamics in continuous-time PGG. Experimentation with the agent-based model generated dynamics that are not presented in discrete-time setting. Thus, it is important to study both discrete and continuous time PGG, with laboratory experiment and ABMS. Our new framework allows to do the latter in a structured way. With the ABOOMS framework, economists can develop PGG simulation models in a structured way and communicate them with a formal model specification. The thesis also showed that there is a need for further investigation on behaviours in continuous-time PGG. For future works, the framework can be tested with variations of PGG or other related strategic interactions.
Computational Markets to Regulate Mobile-Agent Systems
… Agents and Multi-Agent …, 2003
Mobile-agent systems allow applications to distribute their resource consumption across the network. By prioritizing applications and publishing the cost of actions, it is possible for applications to achieve faster performance than in an environment where resources are evenly shared. We enforce the costs of actions through markets, where user applications bid for computation from host machines.
… Behavioral Economics And Experimental Economics of …, 2007
In "Skating on Thin Ice," Frohlich and Oppenheimer (2006) describe a phenomenon they observed in laboratory experiments on the production of public goods that is rarely discussed in the literature. They report individual contributions to the public good are often inconsistent over time, appearing to fluctuate between two distinct contribution levels. Although they conjecture that individuals have complex context-dependent preferences, they did not develop a full specification of the theory. We develop an agent-based simulation of these conjectures, provide a possible specification of a theory of complex context-dependent preferences, and demonstrate how this theory can, in fact, generate the pattern of contributions observed by Frohlich and Oppenheimer. We then conduct sensitivity analyses, examining the behavior generated by fourteen scenarios. Two main theories are considered: that inconsistent contributions arise either from a deterministic avoidance of exploitation or from a probabilistic response to exploitation. The former theory clearly fails, the latter theory, under certain conditions, does produce the observed pattern of contributions. Two simple alternative theories are also considered, that of a highly-stylized "probabilistic guilt" and of goal-oriented but non-utility maximizing behavior (with stable preferences). Both alternatives, under certain conditions, are also able to generate the observed pattern. We develop an analysis of situations in which the predictions of these theories diverge and suggest that one could discriminate between them in laboratory settings. Finally, we consider a possibly fruitful relationship between simulation and experimentation to consider the implications of one's models and conjectures.
A Mobile Agent-Based Electronic Marketplace
2001
The electronic marketplace is a new medium for exchanging information, goods, services, and payments. The marketplace houses infrastructure, facilitates transactions, and matches buyers with sellers. An agent-based marketplace allows corporate data to be maintained by local buyers and sellers and transferred to the marketplace only when orders are matched. This provides participating companies with autonomy and independence. This study proposes a framework of using the mobile agent to demonstrate autonomous behavior in the electronic marketplace.
2007
In "Skating on Thin Ice," Frohlich and Oppenheimer (2006) describe a phenomenon they observed in laboratory experiments on the production of public goods that is rarely discussed in the literature. They report individual contributions to the public good are often inconsistent over time, appearing to fluctuate between two distinct contribution levels. Although they conjecture that individuals have complex context-dependent preferences, they did not develop a full specification of the theory. We develop an agent-based simulation of these conjectures, provide a possible specification of a theory of complex context-dependent preferences, and demonstrate how this theory can, in fact, generate the pattern of contributions observed by Frohlich and Oppenheimer. We then conduct sensitivity analyses, examining the behavior generated by fourteen scenarios. Two main theories are considered: that inconsistent contributions arise either from a deterministic avoidance of exploitation or from a probabilistic response to exploitation. The former theory clearly fails, the latter theory, under certain conditions, does produce the observed pattern of contributions. Two simple alternative theories are also considered, that of a highly-stylized "probabilistic guilt" and of goal-oriented but non-utility maximizing behavior (with stable preferences). Both alternatives, under certain conditions, are also able to generate the observed pattern. We develop an analysis of situations in which the predictions of these theories diverge and suggest that one could discriminate between them in laboratory settings. Finally, we consider a possibly fruitful relationship between simulation and experimentation to consider the implications of one's models and conjectures.
A multi-agent system for electronic commerce including adaptive strategic behaviours
1999
This work is primarily based on the use of software agents for automated negotiation. We present in this paper a test-bed for agents in an electronic marketplace, through which we simulated different scenarios allowing us to evaluate different agents' negotiation behaviours. The system follows a multi-party and multi-issue negotiation approach.
Evaluating the cost of enforcement by agent-based simulation: A wireless mobile grid example
2013
The subject of this paper is the cost of enforcement, to which we take a satisficing approach through the examination of marginal cost-benefit ratios. Social simulation is used to establish that less enforcement can be beneficial overall in economic terms, depending on the costs to system and/or stakeholders arising from enforcement. The results are demonstrated by means of a case study of wireless mobile grids (WMGs). In such systems the dominant strategy for economically rational users is to free-ride, i.e. to benefit from the system without contributing to it. We examine the use of enforcement agents that police the system and punish users that take but do not give. The agent-based simulation shows that a certain proportion of enforcement agents increases cooperation in WMG architectures. The novelty of the results lies in our empirical evidence for the diminishing marginal utility of enforcement agents: that is how much defection they can foreclose at what cost. We show that an increase in the number of enforcement agents does not always increase the overall benefits-cost ratio, but that with respect to satisficing, a minimum proportion of enforcement agents can be identified that yields the best results.
Public Goods Game Simulator with Reinforcement Learning Agents
2010 Ninth International Conference on Machine …, 2010
As a famous game in the domain of game theory, both pervasive empirical studies as well as intensive theoretical analysis have been conducted and performed worldwide to research different public goods game scenarios. At the same time, computer game simulators are utilized widely for better research of game theory by providing easy but powerful visualization and statistics functionalities. However, although solutions of public goods game have been widely discussed with empirical studies or theoretical approaches, no computational and automatic simulation approaches has been adopted. For this reason, we have implemented a computer simulator with reinforcement learning agents module for public goods game, and we have utilized this simulator to further study the characteristics of public goods game. Furthermore, in this article, we have also presented a bunch of interesting experimental results with respect to the strategies that agents used and the profits they earned.
A real-life experiment in creating an agent marketplace
Software Agents and Soft Computing Towards Enhancing Machine Intelligence, 1997
Software agents help people with time consuming activities. One increasingly popular application for software agents is electronic commerce, namely having agents buy and sell goods and services on behalf of users. We recently conducted a real-life experiment in creating an agent marketplace, using a slightly modified version of the Kasbah system [Chavez96]. Approximately 200 participants intensively interacted with the system over a one-day, six-hour period. This paper describes the setup of the experiment, the architecture of the electronic market and the behaviors of the agents. We discuss the rationale behind the design decisions and analyze the results obtained. We conclude with a discussion of current experiments involving thousands of users interacting with the agent marketplace over a long period of time, and speculate on the long-range impact of this technology upon society and the economy.