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Importance of Voluntary behavior, attention control To attain cognitive behavior - Toward future cognitive humanoid robot Takamasa Koshizen Honda Research.

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Presentation on theme: "Importance of Voluntary behavior, attention control To attain cognitive behavior - Toward future cognitive humanoid robot Takamasa Koshizen Honda Research."— Presentation transcript:

1 Importance of Voluntary behavior, attention control To attain cognitive behavior - Toward future cognitive humanoid robot Takamasa Koshizen Honda Research Institute Japan Inc. Workshop of DC-Tales (Santorini), June. 3

2 Content Part 1: Humanoid robot - Asimo Part 2: Basic concept model Part 3: Application concept model Cf. We will have brief demo (video) of our robot

3 Humanoid robot Brain-like technology represented as attention and cross-modal integration allows the humanoid robot to obtain social cognitive aspects of human-like behavior -Highly kinematic behavior -Multimodal communication - Social Cognitive feature

4 PFC-ACC Interaction PFC-ACC interaction playing a key role in cognitive control by monitoring for occurrence of response conflict. ACC response conflict situations across mutiple modalities. Voluntary Behavioral Selection Based on Reward (Shima et al, 2000)

5 Prefrontal cortex - Prefrontal cortex (PFC), neocortex region - most elaborated in primates, animals for taking diverse and flexible - PFC is NOT critical for performing simple, automatic behavior to an unexpected sound or movement - By contrast, PFC is important when the ‘top-down’ processing is needed - when behavior must be induced by internal states or intentions. Rainer G. and Miller, E.K, 1999 Statistical Nature !! Preparation of Forcoming Actions! Pochon et al., 2001

6 Basic model concept Hikosaka et al., 1998

7 Learning scheme Learning schemes to combine two different criteria, dedicated from subcortical and neocortical region in the brain Learning schemes are 1.Reinforcement learning 2.Supervised learning 3.Statistical learning How it could be merged the different criteria by the learning scheme?

8 Target detection Bottom-upTop-down Bayesian Update Koshizen et al., 2000

9 Self-motion estimates Koshizen et al., 2001

10 Cross Supramodality  w 1 1  ε大ε大 ε小ε小 Hardware design to rewiring mechanism for cross-modal integration  =∫ w・ ρds Koshizen et al., 2002

11 Critical Period and Rewiring Critical period for establishing the binocular system is not only the matter of binding visual form and motion to form representation of a visible object, but also the matter of semantic understanding of object. How brain distinguish between the resemble objects that end up classified into otherwise different groups? Proposed cross-modal rewiring system provides the hypothetical computation that each heterosensory modality is intrinsically bound, and the rewiring (inhibitory) network yields thus the functional meaning of their sensory inputs by calculating. The two-typed supramodality such as motion and form. Hensch et al., 1998 A particular class of inhibitory connection emerged within Neocortex during the crerical period, to bring visual sensitivity

12 Application model concept Ecological behavior Complex Kinematic Capability Basic emotion and expression Visuoarditory interaction Basic Model Concept

13 Biological Motion 動態視覚 Dorsal 形態視覚 MT PPC V1 PIT V4 V2 ITC Ventral STS

14 Component learning

15 Growing component

16 Hierarchical system Expectation : Few components in a face could endow to best represent hidden variables (indicator components), which are employed to specify and identify the person Koshizen et al., 2003

17 Complex kinematic feature

18 Mechanical designing This action is supported by a passive flexible spinal cord that is realized via a spring/motor combination connection the lower body to the upper body. This passive spring system provides additional forward thrust and support in fast forward motion. Similar to the bending spinal cord of a cheetah during fast running Picture of the raw material for artificial skin. The material is available in various thickness (object shown here is 3mm). This could be liable for a robot of approx. 5 to 10 kg weight. artificial skin is used as stabilizing pressure sensor

19 Conclusion -A-priori knowledge or selection criteria – voluntary behavior The approach of a purely AI system or a purely ANN system in practice leads to non-satisfactory results. A hybrid construction of both criteria and flexibility -Multimodal interaction makes easier to sophisticate the knowledge and selection criteria Interaction/learning/evolvement of the system will lead to better criteria settings. For the system as well as creation of new criteria which in turn excelled the behavioral mechanism (In this sense, attention considers the predominant role of attention as shaping behavior motor output). -Cognitive function may be attained by extremely complex kinematics capabilities such as grasping for objects, bending down and up, sitting down on objects. Such complex kinematic feature provides frequent interaction among polymodal stimuli. Attention will need to be mediated for segregating the important/non-important -Statistical Nature of prefrontal cortex could be mechanism for making the selections, as suggested the paper by Miller et al. (1999) -Expectation is one of candidates for the criteria of top-down attention control

20 Future prospects Voluntary behavior and the extremely complex kinematics capabilities is the basis for the emergence of cognitive functionality Motor Control Expectant function How the criteria (ex. Expectation) can be converged the different local criterions between intrinsic bound (subcortical) and experience dependency (cortical), through attention mediated from prefrontral cortex. Koshizen et al, 2002 Kirchner et al., 2002

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