Integration of sensorimotor mappings by making use of redundancies

Hemion N, Joublin F, Rohlfing K. Integration of sensorimotor mappings by making use of redundancies. In: IEEE Computational Intelligence Society, Institute of Electrical and Electronics Engineers, eds. The 2012 International Joint Conference on Neural Networks (IJCNN). Brisbane, Australia: IEEE; 2012

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations

Building Blocks for Cognitive Robots: Embodied Simulation and Schemata in a Cognitive Architecture

Hemion N. Building Blocks for Cognitive Robots: Embodied Simulation and Schemata in a Cognitive Architecture. Bielefeld: Bielefeld University; 2013.Building robots with the ability to perform general intelligent action is a primary goal of artificial intelligence research. The traditional approach is to study and model fragments of cognition separately, with the hope that it will somehow be possible to integrate the specialist solutions into a functioning whole. However, while individual specialist systems demonstrate proficiency in their respective niche, current integrated systems remain clumsy in their performance. Recent findings in neurobiology and psychology demonstrate that many regions of the brain are involved not only in one but in a variety of cognitive tasks, suggesting that the cognitive architecture of the brain uses generic computations in a distributed network, instead of specialist computations in local modules. Designing the cognitive architecture for a robot based on these findings could lead to more capable integrated systems. In this thesis, theoretical background on the concept of embodied cognition is provided, and fundamental mechanisms of cognition are discussed that are hypothesized across theories. Based on this background, a view of how to connect elements of the different theories is proposed, providing enough detail to allow computational modeling. The view proposes a network of generic building blocks to be the central component of a cognitive architecture. Each building block learns an internal model for its inputs. Given partial inputs or cues, the building blocks can collaboratively restore missing components, providing the basis for embodied simulation, which in theories of embodied cognition is hypothesized to be a central mechanism of cognition and the basis for many cognitive functions. In simulation experiments, it is demonstrated how the building blocks can be autonomously learned by a robot from its sensorimotor experience, and that the mechanism of embodied simulation allows the robot to solve multiple tasks simultaneously. In summary, this thesis investigates how to develop cognitive robots under the paradigm of embodied cognition. It provides a description of a novel cognitive architecture and thoroughly discusses its relation to a broad body of interdisciplinary literature on embodied cognition. This thesis hence promotes the view that the cognitive system houses a network of active elements, which organize the agent's experiences and collaboratively carry out many cognitive functions. On the long run, it will be inevitable to study complete cognitive systems such as the cognitive architecture described in this thesis, instead of only studying small learning systems separately, to answer the question of how to build truly autonomous cognitive robots

Justifications for a Discontinuity Theory of Language Evolution

In Chapter 6 of Biological Foundations of Language, Lenneberg argues against continuity theories of language evolution, which claim that language evolved from simpler communication systems. Although Lenneberg was pessimistic about even discontinuity theories explaining how language evolved, discontinuity has become significant in the Minimalist program, which posits that our species’ acquisition of Merge was the key discontinuity that made language possible. On the basis of a unified description of natural communication systems, I show that language is indeed based upon a cognitive discontinuity, which is moreover specific to linguistic ability. However, I argue that even Minimalist theories must recognise this discontinuity as the sensorimotor interface with syntax, rather than syntax itself. This ultimately supports the view that syntactic structures are structures of thought, but taking this claim seriously means reimagining how syntax relates to semantics and morphology, as the traditional ‘lexical item’ is no longer a tenable primitive of generative theory

Final report key contents: main results accomplished by the EU-Funded project IM-CLeVeR - Intrinsically Motivated Cumulative Learning Versatile Robots

This document has the goal of presenting the main scientific and technological achievements of the project IM-CLeVeR. The document is organised as follows: 1. Project executive summary: a brief overview of the project vision, objectives and keywords. 2. Beneficiaries of the project and contacts: list of Teams (partners) of the project, Team Leaders and contacts. 3. Project context and objectives: the vision of the project and its overall objectives 4. Overview of work performed and main results achieved: a one page overview of the main results of the project 5. Overview of main results per partner: a bullet-point list of main results per partners 6. Main achievements in detail, per partner: a throughout explanation of the main results per partner (but including collaboration work), with also reference to the main publications supporting them

Justifications for a Discontinuity Theory of Language Evolution

In Chapter 6 of Biological Foundations of Language, Lenneberg argues against continuity theories of language evolution, which claim that language evolved from simpler communication systems. Although Lenneberg was pessimistic about even discontinuity theories explaining how language evolved, discontinuity has become significant in the Minimalist program, which posits that our species’ acquisition of Merge was the key discontinuity that made language possible. On the basis of a unified description of natural communication systems, I show that language is indeed based upon a cognitive discontinuity, which is moreover specific to linguistic ability. However, I argue that even Minimalist theories must recognise this discontinuity as the sensorimotor interface with syntax, rather than syntax itself. This ultimately supports the view that syntactic structures are structures of thought, but taking this claim seriously means reimagining how syntax relates to semantics and morphology, as the traditional ‘lexical item’ is no longer a tenable primitive of generative theory

Justifications for a Discontinuity Theory of Language Evolution

In Chapter 6 of Biological Foundations of Language, Lenneberg argues against continuity theories of language evolution, which claim that language evolved from simpler communication systems. Although Lenneberg was pessimistic about even discontinuity theories explaining how language evolved, discontinuity has become significant in the Minimalist program, which posits that our species’ acquisition of Merge was the key discontinuity that made language possible. On the basis of a unified description of natural communication systems, I show that language is indeed based upon a cognitive discontinuity, which is moreover specific to linguistic ability. However, I argue that even Minimalist theories must recognise this discontinuity as the sensorimotor interface with syntax, rather than syntax itself. This ultimately supports the view that syntactic structures are structures of thought, but taking this claim seriously means reimagining how syntax relates to semantics and morphology, as the traditional ‘lexical item’ is no longer a tenable primitive of generative theory

From locomotion to cognition: Bridging the gap between reactive and cognitive behavior in a quadruped robot

The cognitivistic paradigm, which states that cognition is a result of computation with symbols that represent the world, has been challenged by many. The opponents have primarily criticized the detachment from direct interaction with the world and pointed to some fundamental problems (for instance the symbol grounding problem). Instead, they emphasized the constitutive role of embodied interaction with the environment. This has motivated the advancement of synthetic methodologies: the phenomenon of interest (cognition) can be studied by building and investigating whole brain-body-environment systems. Our work is centered around a compliant quadruped robot equipped with a multimodal sensory set. In a series of case studies, we investigate the structure of the sensorimotor space that the application of different actions in different environments by the robot brings about. Then, we study how the agent can autonomously abstract the regularities that are induced by the different conditions and use them to improve its behavior. The agent is engaged in path integration, terrain discrimination and gait adaptation, and moving target following tasks. The nature of the tasks forces the robot to leave the ``here-and-now'' time scale of simple reactive stimulus-response behaviors and to learn from its experience, thus creating a ``minimally cognitive'' setting. Solutions to these problems are developed by the agent in a bottom-up fashion. The complete scenarios are then used to illuminate the concepts that are believed to lie at the basis of cognition: sensorimotor contingencies, body schema, and forward internal models. Finally, we discuss how the presented solutions are relevant for applications in robotics, in particular in the area of autonomous model acquisition and adaptation, and, in mobile robots, in dead reckoning and traversability detection