Abstract The frame problem is a problem that arises when an agent attempts to assess the consequences of future behaviour. Strictly, it is a problem of modelling that arises during planning. The problem arises because many of the possible consequences of a planned action are not really relevant to the decision whether to perform the action. The frame problem is typical of the classical approach to artificial intelligence, but it is evident that animals do not suffer from this problem. In (...) this paper it is suggested that animals can circumvent the frame problem because their decision?making architecture is very different from that traditionally used in artificial intelligence. (shrink)

Insects have small brains and heuristics or ‘rules of thumb’ are proposed here to be a good model for how insects optimize the objects they make and use. Generally, heuristics are thought to increase the speed of decision making by reducing the computational resources needed for making decisions. By corollary, heuristic decisions are also deemed to impose a compromise in decision accuracy. Using examples from object optimization behavior in insects, we will argue that heuristics do not inevitably imply a lower (...) computational burden or lower decision accuracy. We also show that heuristic optimization may be driven by certain features of the optimization problem itself: the properties of the object being optimized, the biology of the insect, and the properties of the function being optimized. We also delineate the structural conditions under which heuristic optimization may achieve accuracy equivalent to or better than more fine-grained and onerous optimization methods. (shrink)

Abstract In this paper we address three concepts that are much talked about in the animal robotics community. These concepts are (1) representations, (2) goals, and (3) minimal cognition. We want to distinguish between information as an objective commodity and representation as something which involves a user, i.e. a system which accesses and uses information. Information per se lies out there and exists independently of any system that makes use of it. Representations presuppose design and require a user. We want (...) to distinguish different kinds of purposive behaviour, which involve different notions of goals, which themselves appear to be different from the point of view of the agent, the designer and the naive observer. We want to try to define cognition in terms of the minimal criteria that would be acceptable in view of our definitions of representations and goals. We recognise that full?blown cognition may require ingredients other than those of minimal cognition. (shrink)