Perceptual Generalization and Context in a Network MemoryInspired Long-Term Memory for Artificial Cognition

Abstract: In the framework of open-ended learning cognitive architectures for robots, this paper deals with thedesign of a Long-Term Memory (LTM) structure that can accommodate the progressive acquisition ofexperience-based decision capabilities, or what different authors call “automation” of what is learnt, asa complementary system to more common prospective functions. The LTM proposed here provides fora relational storage of knowledge nuggets given the form of artificial neural networks (ANNs) that isrepresentative of the contexts in which they are relevant in a configural associative structure. It alsoaddresses the problem of continuous perceptual spaces and the task- and context-related generalizationor categorization of perceptions in an autonomous manner within the embodied sensorimotor apparatusof the robot. These issues are analyzed and a solution is proposed through the introduction of two newtypes of knowledge nuggets: P-nodes representing perceptual classes and C-nodes representing contexts.The approach is studied and its performance evaluated through its implementation and application to areal robotic experimentXunta de Galicia; ED431C 2017/12Xunta de Galicia; ED341D R2016/01

A perspective on lifelong open-ended learning autonomy for robotics through cognitive architectures

[Abstract]: This paper addresses the problem of achieving lifelong open-ended learning autonomy in robotics, and how different cognitive architectures provide functionalities that support it. To this end, we analyze a set of well-known cognitive architectures in the literature considering the different components they address and how they implement them. Among the main functionalities that are taken as relevant for lifelong open-ended learning autonomy are the fact that architectures must contemplate learning, and the availability of contextual memory systems, motivations or attention. Additionally, we try to establish which of them were actually applied to real robot scenarios. It transpires that in their current form, none of them are completely ready to address this challenge, but some of them do provide some indications on the paths to follow in some of the aspects they contemplate. It can be gleaned that for lifelong open-ended learning autonomy, motivational systems that allow finding domain-dependent goals from general internal drives, contextual long-term memory systems that all allow for associative learning and retrieval of knowledge, and robust learning systems would be the main components required. Nevertheless, other components, such as attention mechanisms or representation management systems, would greatly facilitate operation in complex domains.Ministerio de Ciencia e Innovación; PID2021-126220OB-I00Xunta de Galicia; EDC431C-2021/39Consellería de Cultura, Educación, Formación Profesional e Universidades; ED431G 2019/0

DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics

Robots are still limited to controlled conditions, that the robot designer knows with enough details to endow the robot with the appropriate models or behaviors. Learning algorithms add some flexibility with the ability to discover the appropriate behavior given either some demonstrations or a reward to guide its exploration with a reinforcement learning algorithm. Reinforcement learning algorithms rely on the definition of state and action spaces that define reachable behaviors. Their adaptation capability critically depends on the representations of these spaces: small and discrete spaces result in fast learning while large and continuous spaces are challenging and either require a long training period or prevent the robot from converging to an appropriate behavior. Beside the operational cycle of policy execution and the learning cycle, which works at a slower time scale to acquire new policies, we introduce the redescription cycle, a third cycle working at an even slower time scale to generate or adapt the required representations to the robot, its environment and the task. We introduce the challenges raised by this cycle and we present DREAM (Deferred Restructuring of Experience in Autonomous Machines), a developmental cognitive architecture to bootstrap this redescription process stage by stage, build new state representations with appropriate motivations, and transfer the acquired knowledge across domains or tasks or even across robots. We describe results obtained so far with this approach and end up with a discussion of the questions it raises in Neuroscience

Motivation as a Tool for Designing Lifelong Learning Robots

[Abstract] Designing robots has usually implied knowing beforehand the tasks to be carried out and in what domains. However, in the case of fully autonomous robots this is not possible. Autonomous robots need to operate in an open-ended manner, that is, deciding on the most interesting goals to achieve in domains that are not known at design time. This obviously poses a challenge from the point of view of designing the robot control structure. In particular, the main question that arises is how to endow the robot with a designer defined purpose and with means to translate that purpose into operational decisions without any knowledge of what situations the robot will find itself in. In this paper, we provide a formalization of motivation from an engineering perspective that allows for the structured design of purposeful robots. This formalization is based on a definition of the concepts of robot needs and drives, which are related through experience to the appropriate goals in specific domains. To illustrate the process, a motivational system to guide the operation of a real robot is constructed using this approach. A series of experiments carried out over it are discussed providing some insights on the design of purposeful motivated operation.This work was partially funded by the EU’s H2020 research programme (grant No 640891 DREAM), Ministerio de Ciencia, Innovación y Universidades of Spain/FEDER (grant RTI2018-101114-B-I00), Xunta de Galicia and FEDER (grant ED431C 2017/12), and by the Spanish Ministry of Education, Culture and Sports through the FPU grant of Alejandro RomeroXunta de Galicia; ED431C 2017/1

Creativity, imagery and schizotypy: an exploration of similarities in cognitive processing

The aims of this thesis were twofold: the first was to develop a reliable and valid measure of the control of mental imagery, second was to explore the links between imagery, creativity and schizotypy. The Image Control and Recognition Task (ICRT) was developed because a reliable and objective measure of mental imagery control was lacking in the field. Two trend analyses (n = 29 and 31) found the tool to effectively measure individual differences in imagery control and the ability to reinterpret mental images. A series of related studies using over 300 participants investigated the construct validity and reliability of the ICRT and found that it provided an accurate measure of both mental imagery control and image recognition, and revealed these to be related, yet distinct dimensions of mental imagery. The tool may be used to indicate abilities on a number of imagery control abilities which appear to be related to enhanced creative performance, such as evocation, rotation, maintenance and transformation. An investigation with 96 psychology students looked into interrelationships between performance-based imagery control (ICRT), self-reported mental imagery abilities (vividness and control) and four dimensions of schizotypy (unusual experiences, cognitive disorganisation, introvertive anhedonia and impulsive nonconformity). A multiple regression found that mental imagery control, unusual experiences and cognitive disorganisation scores together predicted 28% of variance in creativity scores. The final study, which recruited 40 visual artists and 56 psychology students, investigated relationships between mental imagery control, incommodious schizotypal traits, and creative performance as measured by battery of creativity tasks and a self-report measure of creative achievement. Significant differences were revealed between the artist and non-artist groups in their creativity scores, but no significant differences were found between these groups on any index of schizotypy. Independent groups t tests showed that the visual artists had significantly more controlled mental imagery and enhanced recognition abilities when compared to the non-artist group. Multiple linear regression found that mental imagery control and unusual experiences scores, which included associated ratings of distress, distraction, and frequency, both explained variance in levels of creative achievement, suggesting that, together, magical ideation, unusual imaginal and perceptual experiences, and fantasy proneness, as well as the ability to control, manipulate, recombine, reinterpret and “play with” mental images is implicated in achieving “real-world” success in creative domains. Imagery control predicted 8% of the variance in the ability to conceive of conceptually unusual, and strikingly original alien creatures when assessed in experimental settings. The ability to control mental imagery shared predictive power with impulsive nonconformity in generating alternative uses for household objects explaining 10% of the variance. It appears that mental imagery abilities are implicated in creativity as the abilities required to control mental imagery were strongly related to higher performance on measures of divergent thinking, creative strengths, conceptual expansion, and creative achievement. The results support assertions that all constructs are multidimensional and related in differential ways, and tentatively point to the possibility that the associations between unusual experiences, mental imagery and enhanced creative achievement may be explained in terms of controlled and uncontrolled imagery, for indices of unusual experiences may indirectly represent levels of schizotypal imagery

Ecological Sustainability of Regional Development

In June 1987, an important international Workshop was held in Vilnius. Lithuanian SSR on the topic, "Ecological Sustainability of Regional Development". The number of participants was 65, coming from nine countries. Many of the papers dealt with ecological-economic assessment methods used in East European countries for regional development planning. Some of the ideas were quite new to environmental planners from Western Europe, and are of great interest to them. This is one kind of service that IIASA provides very well -- bringing people together and bridging language barriers in the East-West context. IIASA is pleased to be associated with the 1987 Workshop and with these Proceedings