Non-human primate token use shows possibilities but also limitations for establishing a form of currency

Computational Mechanisms Underlying Motivation to Earn Symbolic Reinforcers

Reinforcement learning is a theoretical framework that describes how agents learn to select options that maximize rewards and minimize punishments over time. We often make choices, however, to obtain symbolic reinforcers (e.g., money, points) that are later exchanged for primary reinforcers (e.g., food, drink). Although symbolic reinforcers are ubiquitous in our daily lives, widely used in laboratory tasks because they can be motivating, mechanisms by which they become motivating are less understood. In the present study, we examined how monkeys learn to make choices that maximize fluid rewards through reinforcement with tokens. The question addressed here is how the value of a state, which is a function of multiple task features (e.g., the current number of accumulated tokens, choice options, task epoch, trials since the last delivery of primary reinforcer, etc.), drives value and affects motivation. We constructed a Markov decision process model that computes the value of task states given task features to then correlate with the motivational state of the animal. Fixation times, choice reaction times, and abort frequency were all significantly related to values of task states during the tokens task (n = 5 monkeys, three males and two females). Furthermore, the model makes predictions for how neural responses could change on a moment-by-moment basis relative to changes in the state value. Together, this task and model allow us to capture learning and behavior related to symbolic reinforcement.

Computational mechanisms underlying motivation to earn symbolic reinforcers

Reinforcement learning (RL) is a theoretical framework that describes how agents learn to select options that maximize rewards and minimize punishments over time. We often make choices, however, to obtain symbolic reinforcers (e.g. money, points) that can later be exchanged for primary reinforcers (e.g. food, drink). Although symbolic reinforcers are motivating, little is understood about the neural or computational mechanisms underlying the motivation to earn them. In the present study, we examined how monkeys learn to make choices that maximize fluid rewards through reinforcement with tokens. The question addressed here is how the value of a state, which is a function of multiple task features (e.g. current number of accumulated tokens, choice options, task epoch, trials since last delivery of primary reinforcer, etc.), drives value and affects motivation. We constructed a Markov decision process model that computes the value of task states given task features to capture the motivational state of the animal. Fixation times, choice reaction times, and abort frequency were all significantly related to values of task states during the tokens task (n=5 monkeys). Furthermore, the model makes predictions for how neural responses could change on a moment-by-moment basis relative to changes in state value. Together, this task and model allow us to capture learning and behavior related to symbolic reinforcement.

Information Theory Opens New Dimensions in Experimental Studies of Animal Behaviour and Communication

Over the last 40–50 years, ethology has become increasingly quantitative and computational. However, when analysing animal behavioural sequences, researchers often need help finding an adequate model to assess certain characteristics of these sequences while using a relatively small number of parameters. In this review, I demonstrate that the information theory approaches based on Shannon entropy and Kolmogorov complexity can furnish effective tools to analyse and compare animal natural behaviours. In addition to a comparative analysis of stereotypic behavioural sequences, information theory can provide ideas for particular experiments on sophisticated animal communications. In particular, it has made it possible to discover the existence of a developed symbolic “language” in leader-scouting ant species based on the ability of these ants to transfer abstract information about remote events.

Carrion Crows and Azure-Winged Magpies Show No Prosocial Tendencies When Tested in a Token Transfer Paradigm

To study the evolution of humans' cooperative nature, researchers have recently sought comparisons with other species. Studies investigating corvids, for example, showed that carrion crows and azure-winged magpies delivered food to group members when tested in naturalistic or simple experimental paradigms. Here, we investigated whether we could replicate these positive findings when testing the same two species in a token transfer paradigm. After training the birds to exchange tokens with an experimenter for food rewards, we tested whether they would also transfer tokens to other birds, when they did not have the opportunity to exchange the tokens themselves. To control for the effects of motivation, and of social or stimulus enhancement, we tested each individual in three additional control conditions. We witnessed very few attempts and/or successful token transfers, and those few instances did not occur more frequently in the test condition than in the controls, which would suggest that the birds lack prosocial tendencies. Alternatively, we propose that this absence of prosociality may stem from the artificial nature and cognitive complexity of the token transfer task. Consequently, our findings highlight the strong impact of methodology on animals' capability to exhibit prosocial tendencies and stress the importance of comparing multiple experimental paradigms.

Economic behaviours among non-human primates

Do we have any valid reasons to affirm that non-human primates display economic behaviour in a sufficiently rich and precise sense of the phrase? To address this question, we have to develop a set of criteria to assess the vast array of experimental studies and field observations on individual cognitive and behavioural competences as well as the collective organization of non-human primates. We review a sample of these studies and assess how they answer to the following four main challenges. (i) Do we see any economic organization or institutions emerge among groups of non-human primates? (ii) Are the cognitive abilities, and often biases, that have been evidenced as underlying typical economic decision-making among humans, also present among non-human primates? (iii) Can we draw positive lessons from performance comparisons among primate species, humans and non-humans but also across non-human primate species, as elicited by canonical game-theoretical experimental paradigms, especially as far as economic cooperation and coordination are concerned? And (iv) in which way should we improve models and paradigms to obtain more ecological data and conclusions? Articles discussed in this paper most often bring about positive answers and promising perspectives to support the existence and prevalence of economic behaviours among non-human primates. This article is part of the theme issue 'Existence and prevalence of economic behaviours among non-human primates'.

What behaviour in economic games tells us about the evolution of non-human species' economic decision-making behaviour

In the past decade, there has been a surge of interest in using games derived from experimental economics to test decision-making behaviour across species. In most cases, researchers are using the games as a tool, for instance, to understand what factors influence decision-making, how decision-making differs across species or contexts, or to ask broader questions about species' propensities to cooperate or compete. These games have been quite successful in this regard. To what degree, however, do these games tap into species' economic decision-making? For the purpose of understanding the evolution of economic systems in humans, this is the key question. To study this, we can break economic decision-making down into smaller components, each of which is a potential step in the evolution of human economic behaviour. We can then use data from economic games, which are simplified, highly structured models of decision-making and therefore ideal for the comparative approach, to directly compare these components across species and contexts, as well as in relation to more naturalistic behaviours, to better understand the evolution of economic behaviour and the social and ecological contexts that influenced it. The comparative approach has successfully informed us about the evolution of other complex traits, such as language and morality, and should help us more deeply understand why and how human economic systems evolved. This article is part of the theme issue 'Existence and prevalence of economic behaviours among non-human primates'.