The Neglected Pieces of Designing Collective Decision-Making Processes

Khaluf, Yara; Simoens, Pieter; Hamann, Heiko

doi:10.3389/frobt.2019.00016

Cited by 13 publications

(13 citation statements)

References 67 publications

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“…Requiring prior knowledge about the number of alternatives n may reduce the applicability of such solutions. As well as collectively selecting the best alternative, a decentralized process of decision-making should also include the phase of decentralized discovery of the available alternatives (23,24). Behaviors that proved successful in the voting phase may suffer a drastic reduction of their performance when both discovery and voting phases are considered (18).…”

Section: Introductionmentioning

confidence: 99%

When less is more: Robot swarms adapt better to changes with constrained communication

et al. 2021

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To effectively perform collective monitoring of dynamic environments, a robot swarm needs to adapt to changes by processing the latest information and discarding outdated beliefs. We show that in a swarm composed of robots relying on local sensing, adaptation is better achieved if the robots have a shorter rather than longer communication range. This result is in contrast with the widespread belief that more communication links always improve the information exchange on a network. We tasked robots with reaching agreement on the best option currently available in their operating environment. We propose a variety of behaviors composed of reactive rules to process environmental and social information. Our study focuses on simple behaviors based on the voter model—a well-known minimal protocol to regulate social interactions—that can be implemented in minimalistic machines. Although different from each other, all behaviors confirm the general result: The ability of the swarm to adapt improves when robots have fewer communication links. The average number of links per robot reduces when the individual communication range or the robot density decreases. The analysis of the swarm dynamics via mean-field models suggests that our results generalize to other systems based on the voter model. Model predictions are confirmed by results of multiagent simulations and experiments with 50 Kilobot robots. Limiting the communication to a local neighborhood is a cheap decentralized solution to allow robot swarms to adapt to previously unknown information that is locally observed by a minority of the robots.

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Section: Introductionmentioning

confidence: 99%

When less is more: Robot swarms adapt better to changes with constrained communication

et al. 2021

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“…The use of such network is fundamental for collective decision-making. It is generally exploited at two stages of the process (i) when spreading information on one or multiple stimuli that are initially perceived by a limited number of individuals that are able to trigger the collective decision process—e.g., a predator attack—; and (ii) when spreading the individuals' opinions or choices to achieve consensus (Khaluf et al, 2019a ).…”

Section: Introductionmentioning

confidence: 99%

Adaptive Foraging in Dynamic Environments Using Scale-Free Interaction Networks

2020

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Group interactions are widely observed in nature to optimize a set of critical collective behaviors, most notably sensing and decision making in uncertain environments. Nevertheless, these interactions are commonly modeled using local (proximity) networks, in which individuals interact within a certain spatial range. Recently, other interaction topologies have been revealed to support the emergence of higher levels of scalability and rapid information exchange. One prominent example is scale-free networks. In this study, we aim to examine the impact of scale-free communication when implemented for a swarm foraging task in dynamic environments. We model dynamic (uncertain) environments in terms of changes in food density and analyze the collective response of a simulated swarm with communication topology given by either proximity or scale-free networks. Our results suggest that scale-free networks accelerate the process of building up a rapid collective response to cope with the environment changes. However, this comes at the cost of lower coherence of the collective decision. Moreover, our findings suggest that the use of scale-free networks can improve swarm performance due to two side-effects introduced by using long-range interactions and frequent network regeneration. The former is a topological consequence, while the latter is a necessity due to robot motion. These two effects lead to reduced spatial correlations of a robot's behavior with its neighborhood and to an enhanced opinion mixing, i.e., more diversified information sampling. These insights were obtained by comparing the swarm performance in presence of scale-free networks to scenarios with alternative network topologies, and proximity networks with and without packet loss.

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“…We will inherit methods from intelligent agents, multi-agent systems, and swarm systems [17] to design group coordination and interaction [18], [19]. We plan to focus on developing efficient strategies for collective decisions [20] made by groups of interacting ChronoPilots. Such decisions may be the outcome of a negotiation process to harmonize time perception across the group individuals.…”

Section: Collective Time Perception and Coordinationmentioning

confidence: 99%

ChronoPilot — Modulating Time Perception

Botev

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Hamann

et al. 2021

2021 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

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Although time can be measured objectively, human time perception is remarkably subjective and influenced by cognitive states, individual motivations, and social factors. This malleability of perceived time can be evidenced, for instance, in stressful situations where one might experience a lack of time, while one might lose track of time in more relaxing circumstances. Based on fundamental knowledge from psychology and cognitive science, the ChronoPilot project aims at developing a prototype technology driven by artificial intelligence to extend or compress human subjective time adaptively and whenever required. Mediated-reality approaches, such as virtual and augmented reality, have enormous potential for presenting the users with visual, auditory, and haptic stimulation patterns that directly or indirectly influence their subjective time and which are difficult to reproduce in the real world. Going beyond individual settings, ChronoPilot will also investigate how to coordinate time plasticity in collaborative environments where one group member's actions may affect other members' perception. Different scenarios, where humans alone or humans and robots have to collaborate in realistic and virtual environments, will validate the planned research. In this paper, we present the fundamental concepts of our project ChronoPilot, which is a work in progress.

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The Neglected Pieces of Designing Collective Decision-Making Processes

Cited by 13 publications

References 67 publications

When less is more: Robot swarms adapt better to changes with constrained communication

When less is more: Robot swarms adapt better to changes with constrained communication

Adaptive Foraging in Dynamic Environments Using Scale-Free Interaction Networks

ChronoPilot — Modulating Time Perception

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