Truth-from-Trash Learning and the Mobot Footballer

As natural resources become less abundant, we naturally become more interested in, and more adept at utilisation of waste materials. In doing this we are bringing to bear a ploy which is of key importance in learning | or so I argue in this paper. In thèTruth from Trash' model, learning is viewed as a process which uses environmental feedback to assemble fortuitous sensory predispositions (sensory`trash') into useful, information vehicles, i.e., `truthful' indicators of salient phenomena. The main aim will be to show how a computer implementation of the model has been used to enhance (through learning) the strategic abilities of a simulated, football playing mobot.