Archive for February 11th, 2010


Lovett, M. C. (1998). Choice. In J. R. Anderson, & C. Lebiere (Eds.). The atomic components of thought, 255-296. Mahwah, NJ: Erlbaum.


Lovett, M. C. (1998). Choice. In J. R. Anderson, & C. Lebiere (Eds.). The atomic components of thought, 255-296. Mahwah, NJ: Erlbaum.


In ACT-R theory each production rule is chosen according to the probability that reflects its expected gain E(i) relative to the competitors expected gains E(j). ACT-R chooses the production with the highest expected gain, but because of the noise in evaluation the production with a highest expected gain is chosen only a certain proportion of time. The presented below Conflict Resolution Equatation describes the probability that the a production with its expected gain E(i) will have the highest noise added expected gain

where t controls the noise of the evaluation.  There evaluations of expected gain are computed as the quantity E=PG – C, where P Is estimated probability of achieving the productions goal, G is the value of the goal and C is the cost to be expected in reaching the goal. P is the estimated probability of eventual successes in attaining the goal, it is decomposed into two parts: P=qr, where q is the probability that the production under consideration will achieve intended next state, and t is the probability of achieving the production’s goal given arrival at the intended next state. For practical reasons we can takes q a 1, leaving r as the main quantity to estimate. Under this constraint the r  parameter is important for determining  the choice among competitive productions. When a production’s parameter r Is low it implies that the production tends not to lead to the goal even when it leads to its intended next state, this r low value will be represented in a low P value, which will lead the production to have a low expected gain. In contrast a production with a high likehood of leading to its goal  will have a higher estimated probability of achieving the goal and hence a higher expected gain evaluation.

In ACT-R the value of the production’s r parameter is estimated as:

r = successes/(successes + failures)

The very important improvement made within ACT-R theory of choice is also implementation of decay of successes and failures experiences used in computing expected gain. In other words: more time elapsed from last use of a production rule a r parameter shall be lower.

r(t) = successes (t) /[successes (t) + failures (t)]


where t(j) is defined as how long ago past success of failure was.

The author describes in the article variety of examples proving how much such implementations makes us closer for good description of the human choice.


Rumelhart, D.E. (1980) Schemata: the building blocks of cognition. In: R.J. Spiro etal. (eds) Theoretical Issues in Reading Comprehension, Hillsdale, NJ: Lawrence Erlbaum.


Rumelhart, D.E. (1980) Schemata: the building blocks of cognition. In: R.J. Spiro etal. (eds) Theoretical Issues in Reading Comprehension, Hillsdale, NJ: Lawrence Erlbaum.


One of the most influential theory on schemas and concepts which are crucial issue for a larger cognitive area regarding knowledge is the schema theory. The theory, besides the frame theory (Minksy 1975) is one of the pillars of current cognitive knowledge about schemata. As “Schemata can represent knowledge at all levels-from ideologies and cultural truths to knowledge about the meaning of a particular word, to knowledge about what patterns of excitations are associated with what letters of the alphabet. We have schemata to represent all levels of our experience, at all levels of abstraction. Finally, our schemata are our knowledge. All of our generic knowledge is embedded in schemata.” (Rumelhart 1980).

Schema theory assumes that when individuals obtain knowledge, they attempt to fit that knowledge into some structure in memory that help them make sense of that knowledge. Schema theory proposes that the individuals breakdown information into generalizable chunks which are then categorically stored in the brain for later recall. Schema theory is an active strategy coding technique necessary for facilitating the recall of knowledge. As new knowledge is perceived, it is coded into either a pre-existing schema or organized into a new script. Schemata are organized mental structures that allows the learners to understand and associate what is being presented to them.

According to this theory, schemata represent knowledge about concepts: objects and the relationships they have with other objects, situations, events, sequences of events, actions, and sequences of actions. A simple example is to think of your schema for dog. Within that schema you most likely have knowledge about dogs in general (bark, four legs, teeth, hair, tails) and probably information about specific dogs, such as collies (long hair, large, Lassie) or springer spaniels (English, docked tails, liver and white or black and white, Millie). You may also think of dogs within the greater context of animals and other living things; that is, dogs breathe, need food, and reproduce. Your knowledge of dogs might also include the fact that they are mammals and thus are warm-blooded and bear their young as opposed to laying eggs. Depending upon your personal experience, the knowledge of a dog as a pet

(domesticated and loyal) or as an animal to fear (likely to bite or attack) may be a part of your schema. And so it goes with the development of a schema. Each new experience corporates more information into one’s schema.


The theory assumes how a knowledge is acquired and stored In the cognitive architecture. Such theories as the above one or the frame theory (Minsky 1975) allow to think seriously about computer simulation of larger areas of the human cognition. This ability gives us much more; we have more and more deterministic knowledge about human cognition. Independently from the above such theories are very useful for any discipline dealing with knowledge and schemas. Nowdays it is difficult to  discuss about conceptual schemes in law and ethics without referring to the above mentioned influential scheme theories.



Minsky, M. 1977. Frame theory. In P.N. Johnson-Laird and P.C.Wason, Thinking: Reasings in Cognitive Science, Cambridge: Cambridge University Press, pp. 355-376.


Minsky, M. 1977. Frame theory. In P.N. Johnson-Laird and P.C.Wason, Thinking: Reasings in Cognitive Science, Cambridge: Cambridge University Press, pp. 355-376.


As the author says: “Here is the essence of the frame theory: When one encounters a new situation (or makes a substantial change in one’s view of a problem), one selects from memory a structure called a frame. This is a remembered framework to be adapted to fit reality by changing details as necessary.” A frame is data structure for representing the stereotyped situation (for example being in the certain kind of living room). Any frame is connected with some kind of information (for example about how to use the frame, what is going to be next, etc). The frame can be imagined as a network of nodes and relations. Top levels of this frame fixed and represent the are always true about supposed situation (personally I think it shall be said not always but with the biggest probability comparing any other knowledge about supposed situation) and lower levels have many terminals – “slots”, that must be filled with specific instances or data. Each terminal can specify the conditions its assignments must meet.

As the author says: “(…) collections of related frames are linked together into frame systems. The effects of important actions are mirrored by transformations between the frames of a system. These are used to make certain kinds of calculations economical, to represent changes of emphasis and attention, and for effectivness of imaginery”.

For example for visual scene analysis, the same scene seen from different perspective is represented by different frames which however are connected with relations of the above mentioned, relevant transformations (in case of non visual kinds of frames of a system differences between frames can represent particular actions, cause effect relation or changes in conceptual viewpoint). Author underline that the crucial point that it makes possible to coordinate information gathered from different viewpoints is that different frames of the system share the same terminals.

Strong point of Minsky’s theory is that it takes into account different expectations and different presumptions. A frame’s terminals are normally already filled with default assignments. Thus a frame m ay contain a many details whose supposition is not specially warranted by the situation. These have many issues in representing general information, most likely cases, techniques for by passing logic and to make useful generalizations. These default assignments are not strongly connected with the subject frame (its terminals), they can be understood as “variables” that described rather the particular situation that the “main stream” frame.

The above main presumption of the frame theory are verified later on in the article in particular cases. The way how knowledge is acquired, represented and organized for future computation according to cognitive science is strongly associated with concepts presented in Minsky’s paper.


The phenomena of cognitive sciences and their up going popularity is they moved forward the border where non scientific discussion starts about human being. By non scientific discussion I mean the discussion where the distance between empiric verified presumption and the philosophical conclusion is really far. Cognitive sciences have made the difference much shorter on many fields oh our knowledge about human beings, about ourselves (about cognition). Especially on the ground of two main pillars of cognitive sciences, AI and psychology, many authors have published their revolutionary articles where bigger and bigger pieces of strict, computable or almost computable, deterministic (in probabilistic way) and  causality knowledge about the mind’s abilities have been presented. Moreover many of such hypothesis are verified from empiric point of view (psychology) and many from biological point of view (neurosciences). Big spots of such knowledge has appeared after famous 1956. One of these important articles was the one presented in 1977 by Marvin Minsky “the pope of AI”. The author described the frames theory, which explained the mechanism of acquisition of knowledge and its representation in way allowing for its potential computable transformation giving the same effects as in the intelligent minds.