Aging Agents

. We are adopting Brooks and Wiley's (1988) view of evolution as an irreversible process capable of producing increasingly greater complexity at higher organizational levels. We depart from the hypothesis that the evolutionary force is intrinsic in the living system and is in reality a continuous senescence function leading gradually and unavoidably to death. We are therefore seeking a senescence function that favors social rather than solitary agents in terms of longevity without prespecifying in detail the agents' life span. We show that a senescence function relying on negative (destructive) feedback links from metabolism to program is in conformity with these specifications. We also show that senescence should affect all the regulation parameters of the agent and that the system remains nonmanipulable and unpredictable as far as its life span is concerned. This senescence function favors the more "cognitive" agent models (the ones having additional regulation loops) and thus the em..

Selection for Attraction

Abstract. In this paper we study the evolutionary potential of a reactive attraction mechanism in a population of agents that interact via cooperation games, as exemplified by the noisy iterated prisoner’s dilemma. Attraction makes an agent unconditionally cooperative toward an attractive opponent, hence introducing a parallel relation between agents, independent from the social interaction context itself, i.e. from the game. An additional partner selection mechanism can exploit such a given psychological condition and discover attracted partners, despite the fact that attraction itself is nowhere represented in the agent reasoning mechanism but is modeled as an uncontrollable process. We show how evolution can select attraction at various levels of increasing complexity and how each level triggers the selection of the next one, provided the corresponding mechanisms emerge behaviorally. We also discuss the implications of these experiments for the study of the evolution of complex cognitive capacities and functionalities

Implementing Reactive Algorithms on a Cellular Control Architecture

This paper deals with a cellular control architecture and the implementation of reactive algorithms on it. Two examples reveal that, to extend a behaviour-based architecture by equipping it with additional reactive algorithms, the arbitration, otherwise action selection, problem has to be redefined in terms of the interaction laws of the algorithms involved. The principles of modularisation and compositionality are proposed as necessary guidelines for reconfigurability. Modularisation refers to the separation of the algorithms from the action selection components and compositionality expresses the concern for modelling the interactions between individual activities. This way, two composition levels are necessary: one at the individual task arousal system and one at the actuators level. For a task considered, the right behavioural grain of activity is the one that minimises those compositionality needs. 1. Introduction The work presented inscribes itself into a larger project which has..

Beyond Cooperation and Competition : Explorations with a Quantitative Tit-For-Tat Model

The modeling of cooperative processes has up to now relied almost exclusively on the traditional cognitivist paradigm, employing explicit representations of goals, beliefs and actions, as seen from an observer's "objective" viewpoint. We present here a quantitative tit-for-tat agent model that is parameterisable, adaptive and scalable. Unlike traditional game theoretic contexts, the kind of social behavioral phenomena we intend to explore shows relativity or subjectivity (the same social situation may be perceived differently by different agents) and dynamicity (if agents are adaptive, an external observer will think the rules of the game change dynamically). This is achieved through the definition of "social" objects or properties, which can be abstract or have a material form, and that are perceivable, accessible and manipulable by the agents. Agents have internal, idiosyncratic motivations that they try to satisfy according to the social feedback. The quantification of the basic t..

Emergence of social networks in systems with attraction, in preparation

Abstract. In this paper we study the effect of a reactive attraction mechanism in a population of agents that can develop partner preferences. We use as base task for agent pair interaction the benchmark IPD game in its noisy version. Attraction makes an agent unconditionally cooperative toward an attractive opponent, hence introducing a parallel relation between agents, independent from the social interaction context itself, i.e. from the game. Partner selection can exploit such a given psychological condition and discover attracted partners, despite the fact that attraction itself is nowhere represented in the agent reasoning mechanism but is modeled as an uncontrollable process. The mechanics of partner selection are studied systematically in simulation

Attraction and Cooperation in Noisy Environments: Individuals and Groups

Abstract. This paper presents an attraction mechanism and its impact on cooperation in a society of agents. We adopt the benchmark setting of the Iterated Prisoner’s Dilemma (IPD, [1]) and we implement attraction as a mechanism that changes the usual agent’s behavior (strategy). More specifically, an agent follows its regular strategy unless it faces an attractive agent. In the latter case, she becomes unconditionally cooperative. This mechanism is shown to yield higher average agent scores in tournaments within uniform or mixed populations than if it were not present. Benefits are higher for higher attraction factors, bigger populations or populations of “irrational” agents. We have also studied the impact of the attraction pairing type and we have found that random not necessarily reciprocal pairing is the best, because even in the absence of reciprocity a rational agent can cooperate consistently with a cooperating attracted, even if irrational, opponent. We have experimented with extreme types of agents as well, namely, a “Don Juan ” agent that is attracted by all others, and a “Sex Symbol ” to whom all others are attracted. Very often, the introduction of a single extreme agent in a society with no other attraction relations may lead to the same result as a regular society with attraction (but without the extreme agent). Finally, we have experimented with groups of interacting agents to identify possible social conditions that enhance cooperation. All our results suggest that psychological mechanisms external to the economic setting can interfere with it and can actually lead to enhanced cooperation and social stability, despite apparent inconsistencies or irrationalities in individual agents behavior. Accordingly, we can sometimes manage some economic systems by manipulating an external social condition that interferes with normal economic behavior