Research Article: High mutual cooperation rates in rats learning reciprocal altruism: The role of payoff matrix

Date Published: January 2, 2019

Publisher: Public Library of Science

Author(s): Guillermo E. Delmas, Sergio E. Lew, B. Silvano Zanutto, Yong Deng.

http://doi.org/10.1371/journal.pone.0204837

Abstract

Cooperation is one of the most studied paradigms for the understanding of social interactions. Reciprocal altruism -a special type of cooperation that is taught by means of the iterated prisoner dilemma game (iPD)- has been shown to emerge in different species with different success rates. When playing iPD against a reciprocal opponent, the larger theoretical long-term reward is delivered when both players cooperate mutually. In this work, we trained rats in iPD against an opponent playing a Tit for Tat strategy, using a payoff matrix with positive and negative reinforcements, that is food and timeout respectively. We showed for the first time, that experimental rats were able to learn reciprocal altruism with a high average cooperation rate, where the most probable state was mutual cooperation (85%). Although when subjects defected, the most probable behavior was to go back to mutual cooperation. When we modified the matrix by increasing temptation rewards (T) or by increasing cooperation rewards (R), the cooperation rate decreased. In conclusion, we observe that an iPD matrix with large positive reward improves less cooperation than one with small rewards, shown that satisfying the relationship among iPD reinforcement was not enough to achieve high mutual cooperation behavior. Therefore, using positive and negative reinforcements and an appropriate contrast between rewards, rats have cognitive capacity to learn reciprocal altruism. This finding allows to infer that the learning of reciprocal altruism has early appeared in evolution.

Partial Text

Altruism is a behavior by an individual that may be to his disadvantage but benefits others individuals. At first sight, Darwin’s natural selection theory does not explain altruistic behavior. Theories have been proposed to account altruist behavior: kin selection [1], group selection and reciprocal altruism [2] among others. In the reciprocal altruism theory, the loss experienced by an individual for being altruist returns later on behalf of the reciprocal partner. Thus, in the long term, being altruist becomes the most useful strategy. In this regard, Triver’s theory of reciprocal altruism explains how natural selection favors reciprocal altruism between non-related individuals. Perhaps the most insightful example of such behavior is the one observed among vampire bats, where individuals share blood with others who have previously shared their food [3].

We trained twelve rats in iPD against an opponent that plays Tit for tat strategy. Tit for tat is based on two simple rules: to cooperate in the first trial and, in the following, to do what the other player (opponent) did in the last trial. Fig 1A shows a schema of the different choices a subject can do in each trial. Thus, when the subject cooperates, it receives one pellet (PR) or eight seconds timeout (PS) depending on whether the opponent choice was to cooperate or to defect. On the other hand, when the subject defects, it receives 2 pellets (PT) or four seconds timeout (PP), according to whether the opponent choice was to cooperate or to defect respectively. The criteria for cooperation was an established preference for pressing C lever (cooperation) over D lever (defection) in more than 60% of the trials for five or more consecutive sessions. Eight out of twelve animals learned to cooperate (cooperation rate 0.86 ± 0.05, mean ± s.e.m), reaching criteria in 30 ± 4 sessions (mean ± s.e.m). In Fig 1B, we show the mean cooperation levels for those animals during the last twenty three sessions before reaching criteria. The inset in Fig 1B shows the mean cooperation level for each animal during the last five training sessions. As a consequence of the increase in cooperation levels, the average total timeout per session decreased as training progressed (0.23 ± 0.08, mean ± sem, see Fig 1C).

In this work, we study the contrasted role between reinforcements in the learning of reciprocal altruism learning in rats. Traditionally, reciprocal altruism is achieved by playing the iterated prisoner’s dilemma game (iPD) when an experimental subject is confronted to a reciprocal opponent. The payoff matrix used has positive and negative reinforcements with high contrasted between positive and negative pairs and also uses discriminating amount of reinforcements [25, 26]. In our experiment, pellets were used as positive reinforcements, and timeout as negative reinforcement. In this way, the positive and negative reinforcements acted as strengtheners of mutual cooperation behavior likelihood [28]. Our results show for the first time high levels of cooperation (86,11%) and mutual cooperation (76,32%) in iPD, (see Fig 1B). Previous published works have taught reciprocity using iPD game, showing that animals prefer short-term benefits or only improve a poor level of cooperation [4, 9, 20, 29, 30]. In other works, authors employed a special treatment to enhance cooperation preference [10, 23, 31, 32]. A possible explanation is that using standard matrices (for example: PT = 6, PR = 4, PP = 1, PS = 0), animals were not able to discriminate between the amount of reinforcement obtained in the long-term in comparison to short-term [24]. For example, if a rat played four sessions [C C C C] he would get 16 pellets, and if played [C D D D] he would get 12 pellets. In our experiment, rats using the same choices earn 4 pellets and no timeout in the first case, and 3 pellets plus a 16 seconds timeout in the second case.

 

Source:

http://doi.org/10.1371/journal.pone.0204837

 

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