Search results for "Internal model"

2019

Despite substantial advances in many different fields of neurorobotics in general, and biomimetic robots in particular, a key challenge is the integration of concepts: to collate and combine research on disparate and conceptually disjunct research areas in the neurosciences and engineering sciences. We claim that the development of suitable robotic integration platforms is of particular relevance to make such integration of concepts work in practice. Here, we provide an example for a hexapod robotic integration platform for autonomous locomotion. In a sequence of six focus sections dealing with aspects of intelligent, embodied motor control in insects and multipedal robots-ranging from comp…

The Attention Schema Theory: A Foundation for Engineering Artificial Consciousness

2017

The purpose of the attention schema theory is to explain how an information-processing device, the brain, arrives at the claim that it possesses a non-physical, subjective awareness, and assigns a high degree of certainty to that extraordinary claim. The theory does not address how the brain might actually possess a non-physical essence. It is not a theory that deals in the non-physical. It is about the computations that cause a machine to make a claim and to assign a high degree of certainty to the claim. The theory is offered as a possible starting point for building artificial consciousness. Given current technology, it should be possible to build a machine that contains a rich internal …

Integrative Biomimetics of Autonomous Hexapedal Locomotion

2019

Despite substantial advances in many different fields of neurorobotics in general, and biomimetic robots in particular, a key challenge is the integration of concepts: to collate and combine research on disparate and conceptually disjunct research areas in the neurosciences and engineering sciences. We claim that the development of suitable robotic integration platforms is of particular relevance to make such integration of concepts work in practice. Here, we provide an example for a hexapod robotic integration platform for autonomous locomotion. In a sequence of six focus sections dealing with aspects of intelligent, embodied motor control in insects and multipedal robots-ranging from comp…

An architecture for observational learning and decision making based on internal models

2013

We present a cognitive architecture whose main constituents are allowed to grow through a situated experience in the world. Such an architectural growth is bootstrapped from a minimal initial knowledge and the architecture itself is built around the biologically-inspired notion of internal models. The key idea, supported by findings in cognitive neuroscience, is that the same internal models used in overt goal-directed action execution can be covertly re-enacted in simulation to provide a unifying explanation to a number of apparently unrelated individual and social phenomena, such as state estimation, action and intention understanding, imitation learning and mindreading. Thus, rather than…

A meta-cognitive architecture for planning in uncertain environments

2013

Abstract The behavior of an artificial agent performing in a natural environment is influenced by many different pressures and needs coming from both external world and internal factors, which sometimes drive the agent to reach conflicting goals. At the same time, the interaction between an artificial agent and the environment is deeply affected by uncertainty due to the imprecision in the description of the world, and the unpredictability of the effects of the agent’s actions. Such an agent needs meta-cognition in terms of both self-awareness and control. Self-awareness is related to the internal conditions that may possibly influence the completion of the task, while control is oriented t…

Learning problem solving skills from demonstration: An architectural approach

2011

We present an architectural approach to learning problem solving skills from demonstration, using internal models to represent problem-solving operational knowledge. Internal forward and inverse models are initially learned through active interaction with the environment, and then enhanced and finessed by observing expert teachers. While a single internal model is capable of solving a single goal-oriented task, it is their sequence that enables the system to hierarchically solve more complex task. Activation of models is goal-driven, and internal ”mental” simulations are used to predict and anticipate future rewards and perils and to make decisions accordingly. In this approach intelligent …

''Forward to the past''

2012

Carlini, Alessandro | Actis-Grosso, Rossana | Stucchi, Natale | Pozzo, Thierry; International audience; ''Our daily experience shows that the CNS is a highly efficient machine to predict the effect of actions into the future; are we so efficient also in reconstructing the past of an action? Previous studies demonstrated we are more effective in extrapolating the final position of a stimulus moving according to biological kinematic laws. Here we address the complementary question: are we more effective in extrapolating the starting position (SP) of a motion following a biological velocity profile? We presented a dot moving upward and corresponding to vertical arm movements that were masked i…

Prédire le passé et le futur : rôle des représentations motrices dans l'inférence du mouvement

2012

The effectiveness of the visual system is permitted by a complex processing network, which relies on cortical, sub-cortical and peripheral structures. The purpose of this research is to improve the knowledge of the process sustaining the visual perception of motion, and to produce a computational model able to reproduce the features of human visual tracking of a moving object.This work includes an extensive bibliographic research, and a series of experiments. The thesis consists of two parts:The first part pertains to the determination of performance in the "backward" inference of a partially visible movement. It consist of defining the involvement of exogenous information (retinal signals)…

Action simulation in the human brain: Twelve questions

2013

Although the idea of action simulation is nowadays popular in cognitive science, neuroscience and robotics, many aspects of the simulative processes remain unclear from empirical, computational, and neural perspectives. In the first part of the article, we provide a critical review and assessment of action simulation theories advanced so far in the wider literature of embodied and motor cognition. We focus our analysis on twelve key questions, and discuss them in the context of human and (occasionally) primate studies. In the second part of the article, we describe an integrative neuro-computational account of action simulation, which links the neural substrate (as revealed in neuroimaging …

Experiments in Artificial Theory of Mind: From Safety to Story-Telling

2018

Theory of mind is the term given by philosophers and psychologists for the ability to form a predictive model of self and others. In this paper we focus on synthetic models of theory of mind. We contend firstly that such models—especially when tested experimentally—can provide useful insights into cognition, and secondly that artificial theory of mind can provide intelligent robots with powerful new capabilities, in particular social intelligence for human-robot interaction. This paper advances the hypothesis that simulation-based internal models offer a powerful and realisable, theory-driven basis for artificial theory of mind. Proposed as a computational model of the simulation theory of …