Building a Science of Animal Minds: Lloyd Morgan, Experimentation, and Morgan’s Canon

Conwy Lloyd Morgan (1852–1936) is widely regarded as the father of modern comparative psychology. Yet, Morgan initially had significant doubts about whether a genuine science of comparative psychology was even possible, only later becoming more optimistic about our ability to make reliable inferences about the mental capacities of non-human animals. There has been a fair amount of disagreement amongst scholars of Morgan’s work about the nature, timing, and causes of this shift in Morgan’s thinking. We argue that Morgan underwent two quite different shifts of attitude towards the proper practice of comparative psychology. The first was a qualified acceptance of the Romanesian approach to comparative psychology that he had initially criticized. The second was a shift away from Romanes’ reliance on systematizing anecdotal evidence of animal intelligence towards an experimental approach, focused on studying the development of behaviour. We emphasize the role of Morgan’s evolving epistemological views in bringing about the first shift – in particular, his philosophy of science. We emphasize the role of an intriguing but overlooked figure in the history of comparative psychology in explaining the second shift, T. Mann Jones, whose correspondence with Morgan provided an important catalyst for Morgan’s experimental turn, particularly the special focus on development. We also shed light on the intended function of Morgan’s Canon, the methodological principle for which Morgan is now mostly known. The Canon can only be properly understood by seeing it in the context of Morgan’s own unique experimental vision for comparative psychology

Mean-Dispersion Preferences and Constant Absolute Uncertainty Aversion

We axiomatize, in an Anscombe-Aumann framework, the class of preferences that admit a representation of the form V(f) = mu - rho(d), where mu is the mean utility of the act f with respect to a given probability, d is the vector of state-by-state utility deviations from the mean, and rho(d) is a measure of (aversion to) dispersion that corresponds to an uncertainty premium. The key feature of these mean-dispersion preferences is that they exhibit constant absolute uncertainty aversion. This class includes many well-known models of preferences from the literature on ambiguity. We show what properties of the dispersion function rho(dot) correspond to known models, to probabilistic sophistication, and to some new notions of uncertainty aversion.Ambiguity aversion, Translation invariance, Dispersion, Uncertainty, Probabilistic sophistication

Bounded rationality and small worlds

We consider conditions under which the representation of the world available to a boundedly rational decision-maker, whose awareness in- creases over time, constitutes an adequate `small world' (in the sense of Savage 1954) for the assessment of a given decision. Equivalently, we consider whether boundedly rational decision-makers who gradu- ally become aware of all relevant contingencies, can pursue a strategy that is sequentially consistent. We derive conditions on beliefs and preferences that yield a separation between the set of propositions of which the boundedly rational decision-maker is aware and those of which she is unaware and show that these conditions are sufficient to ensure sequential consistency.

Probabilistically Sophisticated Multiple Priors.

We characterize the intersection of the probabilistically sophisticated and multiple prior models. We show this class is strictly larger than the subjective expected utility model and that its elements can be generated from a generalized class of the -contaminated priors, which we dub the - contaminated/ -truncated prior.subjective probability, maximin expected utility, epsilon-contamined priors.

Inductive reasoning about unawareness

We develop a model of games with awareness that allows for differential levels of awareness. We show that, for the standard modal logical interpretations of belief and awareness, a player cannot believe there exist propositions of which he is unaware. Nevertheless, we argue that a boundedly rational individual may regard the possibility that there exist propositions of which she is unaware as being supported by inductive reasoning, based on past experience and consideration of the limited awareness of others. In this paper, we provide a formal representation of inductive reasoning in the context of a dynamic game with awareness. We show that, given differential awareness over time and between players, individuals can derive inductive support for propositions expressing their own unawareness.

Learning and Discovery

We formulate a dynamic framework for an individual decision-maker within which discovery of previously unconsidered propositions is possible. Using a standard game-theoretic representation of the state space as a tree structure generated by the actions of agents (including acts of nature), we show how unawareness of propositions can be represented by a coarsening of the state space. Furthermore we develop a semantics rich enough to describe the individual's awareness that currently undiscovered propositions may be discovered in the future. Introducing probability concepts, we derive a representation of ambiguity in terms of multiple priors, reflecting implicit beliefs about undiscovered proposition, and derive conditions for the special case in which standard Bayesian learning may be applied to a subset of unambiguous propositions. Finally, we consider exploration strategies appropriate to the context of discovery, comparing and contrasting them with learning strategies appropriate to the context of justification, and sketch applications to scientific research and entrepreneurship.

The Risk Premium for Equity: Implicatiosn for Resource Allocation, Welfare adn Policy

Analysis of the equity premium puzzle has focused on private sector capital markets. The object of this paper is to consider the welfare and policy implications of each of the broad classes of explanations of the equity premium puzzle. As would be expected, the greater the deviation from the first-best outcome implied by a given explanation of the equity premium puzzle, the more interventionist are the implied policy conclusions. Nevertheless, even explanations of the equity premium puzzle consistent with a general consumption-based asset pricing model have important welfare and policy implications.

Decomposable Choice Under Uncertainty

Savage motivated his Sure Thing Principle by arguing that, whenever an act would be preferred if an event obtains and preferred if that event did not obtain, then it should be preferred overall. The idea that it should be possible to decompose and recompose decision problems in this way has normative appeal. We show, however, that it does not require the full separability across events implicit in Savage's axiom. We formulate a weaker axiom that suffices for decomposability, and show that this implies an implicit additive representation. Our decomposability property makes local necessary conditions for optimality, globally sufficient. Thus, it is useful in computing optimal acts. It also enables Nash behavior in games of incomplete information to be decentralized to the agent-normal form. None of these results rely on probabilistic sophistication; indeed, our axiom is consistent with the Ellsberg paradox. If we assume probabilistic sophistication, however, then the axiom holds if and only if the agent's induced preferences over lotteries satisfy betweenness.Sure-thing principle, decomposability, uncertainty, computation, dynamic programming solvability, agent-normal form games, non-expected utility, betweenness