Commencement Program, June (1939)

https://red.mnstate.edu/commencement/1056/thumbnail.jp

Collective Learning and Optimal Consensus Decisions in Social Animal Groups

<div><p>Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.</p></div

The observational correlation of cues.

<p>(a) Observational correlation describes the degree to which observations made by different group members are independent of each other. A low correlation cue provides group members with independent observations, while a high correlation cue provides just one observation to all group members on a given trial. (b) Exclusive use of a low correlation cue results in a monotonic increase in collective accuracy as group size increases (green solid line), a hallmark of collective wisdom (). In contrast, exclusive use of a low correlation cue shows no increase in collective accuracy with group size (black solid line; ). A mixed strategy, whereby individuals probabilistically choose one of the cues, may lead to collective accuracy greater than that obtained from using either of the cues exclusively when .</p

Flowchart of the collective learning process.

<p>(a) A decision trial begins with individuals observing cues in the environment. In this model we have two cues, one with low observational correlation and one with high correlation. (b) Individuals use the low correlation cue with probability and the high correlation cue with probability in order to form a discrete vote for one of the two options. In the case that both cues indicate the same option, the individual always votes for that option. (c) The votes are aggregated and a consensus decision is made by simple majority rule. (d) The resulting reward or punishment is used to update each individual's voting behavior. A learning rule similar to the Rescorla-Wagner learning rule is used to update the associative strength(s) of the cue(s) that were present at the chosen option. The associative strengths determine and therefore how an individual votes.</p

The learned and optimal behavioral strategies of individuals in a social context, across environmental conditions and group sizes.

<p>(a–d) The mean learned voting behavior (the probability that individuals use the low correlation cue), for all combinations of reliabilities of the low correlation cue () and high correlation cue () for (a) group size (isolated case), (b) , (c) , and (d) . For each environment and group size combination, 500 simulations of 1000 training trials were performed, using a learning rate of , and the mean behavior of the last 100 trials across the simulations is reported. (e–h) The optimal voting behavior for the environments and group sizes shown in (a–d).</p

Electronic supplementary text and figures from Counteracting estimation bias and social influence to improve the wisdom of crowds

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Data from Counteracting estimation bias and social influence to improve the wisdom of crowds

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