Methods, Models, and the Evolution of Moral Psychology

Why are we good? Why are we bad? Questions regarding the evolution of morality have spurred an astoundingly large interdisciplinary literature. Some significant subset of this body of work addresses questions regarding our moral psychology: how did humans evolve the psychological properties which underpin our systems of ethics and morality? Here I do three things. First, I discuss some methodological issues, and defend particularly effective methods for addressing many research questions in this area. Second, I give an in-depth example, describing how an explanation can be given for the evolution of guilt---one of the core moral emotions---using the methods advocated here. Last, I lay out which sorts of strategic scenarios generally are the ones that our moral psychology evolved to `solve', and thus which models are the most useful in further exploring this evolution

Grounding Artificial Intelligence in the Origins of Human Behavior

Recent advances in Artificial Intelligence (AI) have revived the quest for agents able to acquire an open-ended repertoire of skills. However, although this ability is fundamentally related to the characteristics of human intelligence, research in this field rarely considers the processes that may have guided the emergence of complex cognitive capacities during the evolution of the species. Research in Human Behavioral Ecology (HBE) seeks to understand how the behaviors characterizing human nature can be conceived as adaptive responses to major changes in the structure of our ecological niche. In this paper, we propose a framework highlighting the role of environmental complexity in open-ended skill acquisition, grounded in major hypotheses from HBE and recent contributions in Reinforcement learning (RL). We use this framework to highlight fundamental links between the two disciplines, as well as to identify feedback loops that bootstrap ecological complexity and create promising research directions for AI researchers

Cruel to be kind: The role of the evolution of altruistic punishment in sustaining human cooperation in public goods games

People cooperate in public goods games even when an individual’s utility maximizing strategy is to defect. A form of non-institutionalized punishment called altruistic punishment—or strong reciprocity—may explain this cooperative behavior. I consider laboratory experiments of public goods games that provide evidence of altruistic punishment and proximate explanations for that behavior. I also present theories of the evolution of altruistic punishment via group-selection, multi-level selection, and gene and culture co-evolution. Furthermore, I consider criticisms of both laboratory results and evolutionary theories that suggest weaknesses in the current research on altruistic punishment. In sum, we will likely never have a definitive explanation of the origins and evolution of human cooperation. I conclude, however, that altruistic punishment may form an integral part of that trajectory

Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics

Evolutionary game dynamics is one of the most fruitful frameworks for studying evolution in different disciplines, from Biology to Economics. Within this context, the approach of choice for many researchers is the so-called replicator equation, that describes mathematically the idea that those individuals performing better have more offspring and thus their frequency in the population grows. While very many interesting results have been obtained with this equation in the three decades elapsed since it was first proposed, it is important to realize the limits of its applicability. One particularly relevant issue in this respect is that of non-mean-field effects, that may arise from temporal fluctuations or from spatial correlations, both neglected in the replicator equation. This review discusses these temporal and spatial effects focusing on the non-trivial modifications they induce when compared to the outcome of replicator dynamics. Alongside this question, the hypothesis of linearity and its relation to the choice of the rule for strategy update is also analyzed. The discussion is presented in terms of the emergence of cooperation, as one of the current key problems in Biology and in other disciplines.Comment: Review, 48 pages, 26 figure

Cooperation as a causal factor in human evolution: a scientific clarification and analysis of German high school biology textbooks

Many evolutionary anthropologists view cooperation as core to the evolutionary success of our species. Concurrently, many sustainability scientists view cooperation as core to the future sustainable development of our species. When it comes to biology education, however, it is unclear how or if students are being engaged in these scientific perspectives. This article offers an overview of scientific perspectives regarding cooperation as a central causal factor in shaping human behaviour, cognition, and culture during human evolution. Against this background, we analysed 23 German high school biology textbooks with the aim to understand if and how cooperation is presented as a causal factor in human evolution and behaviour. Overall, the role of cooperation, especially the emotional and motivational aspects of cooperative behaviour, and the role of a cooperative social and cultural environment in shaping human traits, appears to be significantly deemphasized compared to the role of individual brain size and ‘intelligence’ in the evolution of our species. Furthermore, in sections on behavioural ecology, humans are hardly ever presented as an example of a highly cooperative species. Overall, textbooks show a diversity of strengths and weaknesses, from which we identify several learning opportunities in the appropriate integration of cooperation science within biology education

How producer biases can favor the evolution of communication: an analysis of evolutionary dynamics

As any other biological trait, communication can be studied under at least four perspectives: mechanistic, ontogenetic, functional, and phylogenetic (Tinbergen, 1963). Here we focus on the following phylogenetic question: how can communication emerge given that both signal-producing and signal-responding abilities seem to be adaptively neutral until the complementary ability is present in the population? We explore the problem of co-evolution of speakers and hearers with artificial life simulations: a population of artificial neural networks evolving a food call system. The core of the paper is devoted to the careful analysis of the complex evolutionary dynamics demonstrated by our simple simulation. Our analyzes reveal an important factor which might solve the phylogenetic problem: the spontaneous production of good (meaningful) signals by speakers due to the need for organisms to categorize their experience in adaptively relevant ways. We discuss our results with respect both to previous simulative work and to the biological literature on the evolution of communication

Evolutionary games on graphs

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first three sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fourth section surveys the topological complications implied by non-mean-field-type social network structures in general. The last three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.Comment: Review, final version, 133 pages, 65 figure