A non-cooperative Pareto-efficient solution to a one-shot Prisoner's Dilemma

The Prisoner's Dilemma is a simple model that captures the essential contradiction between individual rationality and global rationality. Although the one-shot Prisoner's Dilemma is usually viewed simple, in this paper we will categorize it into five different types. For the type-4 Prisoner's Dilemma game, we will propose a self-enforcing algorithmic model to help non-cooperative agents obtain Pareto-efficient payoffs. The algorithmic model is based on an algorithm using complex numbers and can work in macro applications.Comment: 14 pages, 3 figure

Emerging Artificial Societies Through Learning

The NewTies project is implementing a simulation in which societies of agents are expected to de-velop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve environmental challenges by acting collectively. The challenges are in-tended to be analogous to those faced by early, simple, small-scale human societies. This report on work in progress outlines the major features of the system as it is currently conceived within the project, including the design of the agents, the environment, the mechanism for the evolution of language and the peer-to-peer infrastructure on which the simulation runs.Artificial Societies, Evolution of Language, Decision Trees, Peer-To-Peer Networks, Social Learning

Variable time scales, agent-based models, and role-playing games: The PIEPLUE river basin management game

This article presents a specific association of a role-playing game (RPG) and an agent-based model (ABM) aimed at dealing with a large range of time scales. Applications to the field of natural resource management lead one to consider the short time scale of resource use in practice at the same time as the longer ones related to resource dynamics or actors' investments. In their daily practice, stakeholders are translating their long-term strategies, a translation that is contextualized and combined with some cooccurring events. Long-term thinking is required for sustainable use of natural resources, but it should take into account its necessary adaptation on a short time scale. This raises the necessity for tools able to tackle jointly these various time scales. The similarity of architecture between computerized ABMs and RPGs makes them easy to associate in a hybrid tool, targeted at meeting this requirement. The proposition of this article is to allocate the representation of short time scales to computerized ABMs and the long ones to RPGs, while keeping the same static structural conceptual model, shared as a common root by both. This synergy is illustrated with PIEPLUE, an interactive setting tackling water-sharing issues.GESTION DE L'EAU;BASSIN VERSANT;RESSOURCE NATURELLE;MODELE;JEU DE ROLE;SYSTEME MULTIAGENTS;AGENT-BASED MODEL;CASE STUDY OF WATER SHARING;CONCEPTUAL MODEL;HYBRID TOOL;INVESTMENTS;LONG-TERM ISSUES;NATURAL RESOURCE MANAGEMENT;PIEPLUE;PARTICIPATORY MODELING;RESOURCE DYNAMICS;RESOURCE USE;ROLE-PLAYING GAME;STAKEHOLDERS;SUSTAINABLE USE OF NATURAL RESOURCES;TIME-SCALE DIVERSITY;VARIABLE TIME SCALES;WATER MANAGEMENT

Visualizing Coevolution With CIAO Plots

In a previous paper [2], we introduced a number of visualization techniques that we had developed for monitoring the dynamics of artificial competitive co-evolutionary systems. One of these techniques involves evaluating the performance of an individual from the current population in a series of trials against opponents from all previous generations, and visualizing the results as a 2-d grid of shaded cells or pixels: qualitative patterns in the shading can indicate different classes of co-evolutionary dynamic. As this technique involves pitting a Current Individual against Ancestral Opponents, we referred to the visualizations as CIAO plots. Since then, a number of other authors studying the dynamics of competitive co-evolutionary systems have used CIAO plots or close derivatives to help illuminate the dynamics of their systems, and it has become something of a de facto standard visualization technique. In this very brief paper we summarise the rationale for CIAO plots, explain the method of constructing a CIAO plot, and review important recent results that identify significant limitations of this technique