D2.1 Requirements and Specification - CORBYS

D2.1 Requirements and Specification
demonstrate quantitatively the role of information in the sensorimotor loop: the difference in entropy
reduction in the environment that an agent achieves in open-loop and closed-loop mode is limited by the
information that the agent takes in. This is a fundamental limit that holds for any system that can be
probabilistically modelled. It does not depend on any other particulars of the model. As such, it exemplifies
the universality character of information-theoretic descriptions of agents which holds independently of their
computational model. This relevance is universal when it holds to the informational interaction (and all
physical interactions are at the same time informational) of an agent with its environment.
However, the relevance even seems to translate into how biological organisms process information internally
or how information is generally processed in evolutionary context. For instance, evolutionary fitness models
that are suitable to be cast into Kelly Gambling scenarios (Kelly, 1956) can be combined with Howard’s value
of information (Howard, 1966) in a coherent framework (Donaldson-Matasci et al., 2010).
There are indications that the internal processing of sensoric stimuli seems also to be governed by
informational optimality principles. This seems to hold particularly true for neural signals (Rieke et al., 1999,
Laughlin et al., 1998, Parush et al., 2011). The basis for that assumption is partly due to metabolic reasons,
since (Shannon) information processing is metabolically expensive. It is expected that evolutionary pressure
will act as to optimise the information processing channels of an organism (Brenner et al., 2000, Laughlin,
2001, Polani, 2009). Under this hypothesis, an under-exploited informatory channel will either be evolved
away until it is optimally used, or else be increasingly used to improve the utility that can be gained through
its existence. It follows that, in the adaptive equilibrium case, one expects that an existing information
channel for an adapted organism (i.e. an organism that is in a suitable sense of its “informational ecology” in
balance with its environment) will be exploited to its fullest by this organism. It will in general not hold true
for an organism out of balance, i.e. an organism that only recently entered a new ecological niche and did not
yet (on individual as well as on population level) have sufficient time to adapt to that niche.
These assumptions are also consistent with the assumption that sensorimotor abilities of animals and humans
operate on the basis of a Bayesian model (Schrater and Kersten, 2002, Körding and Wolpert, 2004). Evidence
for the Bayesian character of organismic decision making is not limited to higher organisms. In fact, it turns
out that even insect behaviour demonstrates some consistency with Bayesian modelling. An example for that
is the infotaxis model that was introduced by (Vergassola et al., 2007) to model the search behaviour of a male
moth for its female mate through a very sparse, event-based olfactory signal. In this model, isolated
pheromone detection events, through an inverse Bayesian model, and through a seeking behaviour that is
consistent with maximizing information about the location of the mate (named infotaxis by the authors) are
sufficient to reconstruct a search-and-home dynamics that is surprisingly consistent with what is observed as
behaviour of actual moths. It is, of course, not assumed that the male moth is indeed “implementing” a full
Bayesian model and an infotaxis dynamics, and in fact, it is more plausible to assume that the brain of the
organism will in most likeliness implement a proxy or surrogate dynamics that, in the scenarios of relevance
will exhibit infotaxis-analogue behaviour. Nevertheless, the close similarity demonstrates that the assumption
of near Bayes- and information-optimal behaviour provides a powerful model while not necessarily of
mechanisms, but of general character of organismic behaviour generation and the incentives that drive it.
12.2.2 Cognitive Modelling Context
The identification of information-theoretic concepts as governing the behaviour of organisms provides
quantitative pathways towards a systematic modelling of cognitive architectures based on these principles.
However, although information theory is an old and long-established field, its successful use for cognitive
modelling has expanded in a very significant only in the last decade, boosted by a series of advances.
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