Colin Allen

In this paper I argue that selection of the best theory of content is not a matter for mere philosophical reflection on the consequences of each theory for our intuitive judgments about content. Rather, the theories must be judged in a different way that is based on the putative roles of content attribution in the behavioural sciences. The ultimate test of any theory of content will be the success of the sciences that adopt it. Furthermore, alternative semantic theories may be seen as complementary rather than antagonistic. Different approaches to content specification may well be compatible, reflecting different but perhaps equally legitimate explanatory goals.

Teleological terms such as "function" and "design" appear frequently in the biological sciences. Examples of teleological claims include: A (biological) function of stotting by antelopes is to communicate to predators that they have been detected. Eagles' wings are (naturally) designed for soaring. Teleological notions were commonly associated with the pre-Darwinian view that the biological realm provides evidence of conscious design by a supernatural creator. Even after creationist viewpoints were rejected by most biologists there remained various grounds for concern about the role of teleology in biology, including whether such terms are: 1. vitalistic (positing some special "life-force"); 2. requiring backwards causation (because future outcomes explain present traits); 3. incompatible with mechanistic explanation (because of 1 and 2); 4. mentalistic (attributing the action of mind where there is none); 5. empirically untestable (for all the above reasons). Opinions divide over whether Darwin's theory of evolution provides a means of eliminating teleology from biology, or whether it provides a naturalistic account of the role of teleological notions in the science. Many contemporary biologists and philosophers of biology believe that teleological notions are a distinctive and ineliminable feature of biological explanations but that it is possible to provide a naturalistic account of their role that avoids the concerns above. Terminological issues sometimes serve to obscure some widely-accepted distinctions.

Psychology, according to a standard dictionary definition, is the science of mind and behavior. For a major part of the twentieth century, (nonhuman) animal psychology was on a behavioristic track that explicitly denied the possibility of a science of animal mind. While many comparative psychologists remain wedded to behavioristic methods, they have more recently adopted a cognitive, information-processing approach that does not adhere to the strictures of stimulus-response explanations of animal behavior. Cognitive ethologists are typically willing to go much further than comparative psychologists by adopting folk-psychological terms to explain the behavior of nonhuman animals. This different attitudes of many scientists presupposes a distinction between cognitive and mental state attributions that is not commonly articulated. This paper seeks to understand that distinction.

Primatologists generally agree that monkeys lack higher-order intentional capacities related to theory of mind. Yet the discovery of the so-called "mirror neurons" in monkeys suggests to many neuroscientists that they have the rudiments of intentional understanding. Given a standard philosophical view about intentional understanding, which requires higher-order intentionahty, a paradox arises. Different ways of resolving the paradox are assessed, using evidence from neural, cognitive, and behavioral studies of humans and monkeys. A decisive resolution to the paradox requires substantial additional empirical work and perhaps a rejection of the standard philosophical view.

The idea that reasoning is a singular accomplishment of the human species has an ancient pedigree.Yet this idea remains as controversial as it is ancient. Those who would deny reasoning to nonhuman animals typically hold a language-based conception of inference which places it beyond the reach of languageless creatures. Others reject such an anthropocentric conception of reasoning on the basis of similar performance by humans and animals in some reasoning tasks, such as transitive inference. Here, building on the modal similarity theory of Vigo [J Exp Theor Artif Intell, 2008 (in press)], we offer an account in which reasoning depends on a core suite of subsymbolic processes for similarity assessment, discrimination, and categorization. We argue that premise-based inference operates through these subsymbolic processes, even in humans. Given the robust discrimination and categorization abilities of some species of nonhuman animals, we believe that they should also be regarded as capable of simple forms of inference. Finally, we explain how this account of reasoning applies to the kinds of transitive inferences that many nonhuman animals display

Social play is naturally characterized in intentional terms. An evolutionary account of social play could help scientists to understand the evolution of cognition and intentionality. Alexander Rosenberg (1990) has argued that if play is characterized intentionally or functionally, it is not a behavioral phenotype suitable for evolutionary explanation. If he is right, his arguments would threaten many projects in cognitive ethology. We argue that Rosenberg's arguments are unsound and that intentionally and functionally characterized phenotypes are a proper domain for ethological investigation.

In this paper we argue that there is much to learn about “wild justice” and the evolutionary origins of morality – behaving fairly – by studying social play behavior in group-living mammals. Because of its relatively wide distribution among the mammals, ethological investigation of play, informed by interdisciplinary cooperation, can provide a comparative perspective on the evolution of ethical behavior that is broader than is provided by the usual focus on primate sociality. Careful analysis of social play reveals rules of engagement that guide animals in their social encounters. Because of its significance in development, play may provide a foundation of fairness for other forms of cooperation that are advantageous to group living. Questions about the evolutionary roots of cooperation, fairness, trust, forgiveness, and morality are best answered by attention to the details of what animals do when they engage in social play – how they negotiate agreements to cooperate, to forgive, to behave fairly, and to develop trust. We consider questions such as why play fairly? Why did play evolve as it has? Does “being fair” mean being more fit? Do individual variations in play influence an individual’s reproductive fitness? Can we use information about the foundations of moral behavior in animals to help us understand ourselves? We conclude that there is likely to be strong selection for cooperative fair play because there are mutual benefits when individuals adopt this strategy and group stability may also be fostered. Numerous mechanisms have evolved to facilitate the initiation and maintenance of social play, to keep others engaged, so that agreeing to play fairly and the resulting benefits of doing so can be readily achieved.

If fast and frugal heuristics are as good as they seem to be, who needs logic and probability theory? Fast and frugal heuristics depend for their success on reliable structure in the environment. In passive environments, there is relatively little change in structure as a consequence of individual choices. But in social interactions with competing agents, the environment may be structured by agents capable of exploiting logical and probabilistic weaknesses in competitors' heuristics. Aspirations toward the ideal of a demon reasoner may consequently be adaptive for direct competition with such agents.

As arti® cial intelligence moves ever closer to the goal of producing fully autonomous agents, the question of how to design and implement an arti® cial moral agent (AMA) becomes increasingly pressing. Robots possessing autonomous capacities to do things that are useful to humans will also have the capacity to do things that are harmful to humans and other sentient beings. Theoretical challenges to developing arti® cial moral agents result both from controversies among ethicists about moral theory itself, and from computational limits to the implementation of such theories. In this paper the ethical disputes are surveyed, the possibility of a `moral Turing Test ’ is considered and the computational di culties accompanying the diŒerent types of approach are assessed. Human-like performance, which is prone to include immoral actions, may not be acceptable in machines, but moral perfection may be computationally unattainable. The risks posed by autonomous machines ignorantly or deliberately harming people and other sentient beings are great. The development of machines with enough intelligence to assess the eŒects of their actions on sentient beings and act accordingly may ultimately be the most important task faced by the designers of arti® cially intelligent automata.

Cognitive ethology is the comparative study of animal cognition from an evolutionary perspective. As a sub-discipline of biology it shares interest in questions concerning the immediate causes and development of behavior. As a part of ethology it is also concerned with questions about the function and evolution of behavior. I examine some recent work in cognitive ethology, and I argue that the notions of mental content and representation are important to enable researchers to answer questions and state generalizations about the function and volution of behavior.