Anticipation (artificial Intelligence) - Anticipation in Evolution and Cognition

Anticipation in Evolution and Cognition

The anticipation of future states is also a major evolutionary and cognitive advance (Sjolander 1995). Anticipatory agents belonging to Rosen's definition are easy to see in human mental capabilities of taking decisions at a certain time T taking into account the effects of their own actions at different future timescales T+k. However, Rosen (a theoretical biologist) describes ALL living organisms as examples of naturally occurring anticipatory systems, which means that there must be somatic predictive models (meaning, "of the body"; physical) as components within the organization of all living organisms. No mental process is required for anticipation. In his book, Anticipatory Systems, Rosen describes how even single cellular organisms manifest this behavior pattern. It is logical to hypothesize therefore: If it is true that life is anticipatory in this sense, then the evolution of the conscious mind (such as human beings experience) may be a natural concentration and amplification of the anticipatory nature of life, itself.

Machine learning methods started to integrate anticipatory capabilities in an implicit form as in reinforcement learning systems (Sutton & Barto, 1998; Balkenius, 1995) where they learn to anticipate future rewards and punishments caused by current actions (Sutton & Barto, 1998). Moreover, anticipation enhanced performance of machine learning techniques to face with complex environments where agents have to guide their attention to collect important information to act (Balkenius & Hulth, 1999).