Maximization of Potential Information Flow as a Universal Utility for Collective Behaviour

Capdepuy, Philippe; Polani, Daniel; Nehaniv, Chrystopher L.

doi:10.1109/alife.2007.367798

Cited by 32 publications

(30 citation statements)

References 7 publications

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“…We expect this model to extend results in the area of self-organization in collective systems (as has been investigated in [5]). Useful applications of this model also include sensor evolution scenarios, where different sensorimotor apparatus can be evaluated in a given environment and compared on such criteria as stability of perception-action loop model and potential capacity to inject information in future sensoric states.…”

Section: Resultssupporting

confidence: 56%

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Adaptation of the Perception-Action Loop Using Active Channel Sampling

Capdepuy

Polani

Nehaniv

2008

2008 NASA/ESA Conference on Adaptive Hardware and Systems

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During the lifetime of a real world agent or robot, many changes unforeseen at design time can occur. Whether these are due to a change in environmental conditions or to alterations of the embodiment of the robot, flexibility and adaptation are essential qualities that can help it to keep operating in this new situation. This work is based on an information-theoretic approach and introduces an exploration strategy that allows an agent to detect and adapt to changes in its perception-action loop by actively sampling areas of interest. We define the problem of exploring the sensorimotor channel and establish a measure of the distance between the observed and the real model of the channel. An optimal Oracle-based strategy is used to compare performances of the adaptive sampling strategy and a random strategy. Results for different scenarios of change in a binary channel show that the proposed strategy is highly effective in many cases. We also outline principles to adapt this mechanism to the exploration of multiple channels and we give preliminary results for such a scenario.

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Section: Resultssupporting

confidence: 56%

“…As a particularly promising path, the use of empowerment has been suggested [12,13,5], a concept similar to the channel capacity of the external part of the perception-action loop of an agent (we discuss this formally and in detail in Sec. 2).…”

Section: Introductionmentioning

confidence: 99%

Adaptation of the Perception-Action Loop Using Active Channel Sampling

Capdepuy

Polani

Nehaniv

2008

2008 NASA/ESA Conference on Adaptive Hardware and Systems

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“…3. The choice of a fixed starting constellation corresponds to an open-loop control problem, but as this is a one-step scenario, it still allows one to achieve full capacity since the precise state of the MAC channel is known when the action is taken 6 .…”

Section: Spatial Examplementioning

confidence: 99%

“…However, apart from previous work on the ability of empowerment to generate complex spatial organizations [6], the interpretation and use of similar information-theoretic quantities in the case of multi-agent systems has been mostly left aside. This work builds upon recent advances in information theory in order to provide a better understanding of the perception-action loop of multiple agents sharing the same environment and of agents having multiple actuators.…”

Section: Introductionmentioning

confidence: 99%

Perception–action loops of multiple agents: informational aspects and the impact of coordination

2011

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Embodied agents can be conceived as entities perceiving and acting upon an external environment. Probabilistic models of this perception-action loop have paved the way to the investigation of information-theoretic aspects of embodied cognition. This formalism allows (i) to identify information flows and their limits under various scenarios and constraints, and (ii) to use informational quantities in order to induce the self-organization of the agent's behaviour without any externally specified drives. This paper extends the perception-action loop formalism to multiple agents. The multiple-access channel model is presented and used to identify the relationships between informational quantities of two agents interacting in the same environment. The central question investigated in this paper is the impact of coordination. Information-theoretic limits on what can be achieved with and without coordination are identified. For this purpose, different abstract channels are studied, along with a concrete example of agents interacting in space. It is shown that, under some conditions, self-organizing systems based on information-theoretic quantities have a tendency to spontaneously generate coordinated behaviour. Moreover, in the perspective of engineering such systems to achieve specific tasks, these information-theoretic limits put constraints on the amount of coordination that is required to perform the task, and consequently on the mechanisms that underly self-organization in the system.

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“…In a 2007 paper, Capdepuy et al [20] examined how the sharing of information influences empowerment as a trigger for complex collective behaviour. Later [21], they used the notion of multiple-access channels to model simultaneous interaction and relate coordination to information-theoretic limits of control.…”

Section: Introductionmentioning

confidence: 99%

Effects of Anticipation in Individually Motivated Behaviour on Survival and Control in a Multi-Agent Scenario with Resource Constraints

Guckelsberger

Polani

2014

Entropy

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Self-organization and survival are inextricably bound to an agent's ability to control and anticipate its environment. Here we assess both skills when multiple agents compete for a scarce resource. Drawing on insights from psychology, microsociology and control theory, we examine how different assumptions about the behaviour of an agent's peers in the anticipation process affect subjective control and survival strategies. To quantify control and drive behaviour, we use the recently developed information-theoretic quantity of empowerment with the principle of empowerment maximization. In two experiments involving extensive simulations, we show that agents develop risk-seeking, risk-averse and mixed strategies, which correspond to greedy, parsimonious and mixed behaviour. Although the principle of empowerment maximization is highly generic, the emerging strategies are consistent with what one would expect from rational individuals with dedicated utility models. Our results support empowerment maximization as a universal drive for guided self-organization in collective agent systems.

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Maximization of Potential Information Flow as a Universal Utility for Collective Behaviour

Cited by 32 publications

References 7 publications

Adaptation of the Perception-Action Loop Using Active Channel Sampling

Adaptation of the Perception-Action Loop Using Active Channel Sampling

Perception–action loops of multiple agents: informational aspects and the impact of coordination

Effects of Anticipation in Individually Motivated Behaviour on Survival and Control in a Multi-Agent Scenario with Resource Constraints

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