Development Of Cognitive Capabilities Research Articles

Anthropomorphic reasoning about neuromorphic AGI safety

One candidate approach to creating artificial general intelligence (AGI) is to imitate the essential computations of human cognition. This process is sometimes called ‘reverse-engineering the brain’ and the end product called ‘neuromorphic.’ We argue that, unlike with other approaches to AGI, anthropomorphic reasoning about behaviour and safety concerns is appropriate and crucial in a neuromorphic context. Using such reasoning, we offer some initial ideas to make neuromorphic AGI safer. In particular, we explore how basic drives that promote social interaction may be essential to the development of cognitive capabilities as well as serving as a focal point for human-friendly outcomes.

Cognitive Offloading Does Not Prevent but Rather Promotes Cognitive Development.

We investigate the relation between the development of reactive and cognitive capabilities. In particular we investigate whether the development of reactive capabilities prevents or promotes the development of cognitive capabilities in a population of evolving robots that have to solve a time-delay navigation task in a double T-Maze environment. Analysis of the experiments reveals that the evolving robots always select reactive strategies that rely on cognitive offloading, i.e., the possibility of acting so as to encode onto the relation between the agent and the environment the states that can be used later to regulate the agent’s behavior. The discovery of these strategies does not prevent, but rather facilitates, the development of cognitive strategies that also rely on the extraction and use of internal states. Detailed analysis of the results obtained in the different experimental conditions provides evidence that helps clarify why, contrary to expectations, reactive and cognitive strategies tend to have synergetic relationships.

Development of Cognitive Capabilities for Smart Home using a Self-Organizing Fuzzy Neural Network

A smart home requires cognitive assistance to analyze and understand the behavior in this sensory rich environment. In this paper we explore the potential of a self-organizing fuzzy neural network (SOFNN) as a core component of a cognitive system for a smart home environment. We develop a cognitive reasoning module that has the ability to adapt its neuronal structure through adding and pruning of neurons according to the incoming data. The SOFNN rules explore the relations of the inputs and the desired reasoning outputs. The network is trained with realistic synthesized data to show its adaptation capability and is tested with unseen data to validate its cognitive capabilities. We outline the theoretical development and describe the results achieved. This initial implementation of the cognitive module demonstrates the potential of the architecture and will serve as a very important test-bed for future work.

Internal Body Perceptions of Ethiopian Jews Who Emigrated to Israel

Previous research regarding knowledge about internal organs among school-age children tied this knowledge to the development of cognitive capabilities. Studies have rarely considered the impact of culture on this knowledge. The purpose of this study was to examine internal body perceptions among Ethiopian Jews who emigrated to Israel. A total of 65 children (stratified according to age) and 19 adults were interviewed. Findings indicated that Ethiopian children reported fewer body organs than did Western children. Further, Ethiopian children and adults, unlike people from Western societies, did not think about the body in terms of different biophysical functions. Rather, they perceived the body as a holistic system in which a divine providence was responsible for body organs working together harmoniously. Implications of the differing perceptions about internal body organs, health, illness, and treatment are discussed.