Explanation-based generalization (EBG) is a powerful approach to concept formation in which a justifiable concept definition is acquired from a single training example and an underlying theory of how the example is an instance of the concept. Soar is an attempt to build a general cognitive architecture combining general learning, problem solving, and memory capabilities. It includes an independ...

Oyster mushroom production in Mindahan Kidul Village has the potential to be developed and high economic value. The prospect of developing oyster business is quite large which can seen from environmental conditions located on slopes Mount Muria availability raw materials for planting media that are easily obtained abundant sawdust. Partners service activity program MSME AJJ Mushroom problems pr...

Di tengah pandemi Covid-19, banyak pelaku usaha, terutama usaha mikro kecil dan menengah (UMKM), yang mengalami tekanan. Usaha Mikro Kecil Menengah (UMKM) memiliki nama merek THEMIL adalah salah satu UMKM ada di Kemuning Guntung Paikat Banjarbaru Kalimantan Selatan. Ditengah pandemik covid 19 ini masih mampu bertahan bahwa dari hasil pengamatan sementara malah berkembang meningkat dalam hal pen...

Context Concept formation is the process by which generalizations are formed through observation of instances from the environment. These instances are described along a number of attributes, which are selected according to their relevance to the problem or task for which the concepts will be used. The context of a concept learning problem consists of the goals and tasks of the learner, as well...

We study learning scenarios in which multiple learners are involved and “nature” imposes some constraints that force the predictions of these learners to behave coherently. This is natural in cognitive learning situations, where multiple learning problems co-exist but their predictions are constrained to produce a valid sentence, image or any other domain representation. Our theory addresses tw...

In this paper, we firstly describe a novel approach to calculate the Chinese sememe similarity based on the HowNet hierarchical sememe tree. When we calculate the sememe similarity, we not only take Semantic Distance, Node Depth and Semantic Coincidence Degree into consideration, but also propose two impact factors named Node Environment Dense (NED) and Node Layer Ratio (NLR) to optimize the ca...

Future computer vision systems must have the ability to discover new object models. This problem can be addressed by relational concept formation systems, which structure a stream of observations into a taxonomy of discovered concepts. This paper presents a representation for images which is invariant under arbitrary groups of transformations. The discovered models, also being invariant, can be...

Concept learning belongs to the fundamental challenges of educational technology. Contrary to the current trend of designing and implementing contents for various web–based virtual courses, concept learning requires cognitive tools rather than digital materials. We introduce a novel scheme to generate computer games from concept maps made by a teacher or a learner herself. Concept gaming exceed...

In the first part, we extend our results from a previous paper on factorization of residuated lattices to residuated lattices with hedges. In the second part, we show how this result can be applied to the problem of factorization of fuzzy concept lattices with hedges. Our approach is that instead of factorizing the original concept lattice with hedges we construct a new data table with fuzzy va...