fore sight cognitive systems project
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Fore sight Cognitive Systems Project. InterAction Conference “The Connective Tissue” Richard Morris and Lionel Tarassenko. Cognitive Systems A working definition. - PowerPoint PPT PresentationTRANSCRIPT
5th September 2003
Foresight Cognitive Systems Project
InterAction Conference
“The Connective Tissue”Richard Morris and Lionel Tarassenko
Cognitive Systems A working definition
“ Cognitive systems are natural or artificial information processing systems, including those responsible for perception, learning, reasoning, and decision-making, and both communication and action ”
Foresight Cognitive Systems IAC (LT and RGMM)
What this Foresight Project has been about...
It is a project that has been run by scientists and supported by Foresight who have provided the scope for events and activities designed by the communities themselves
Interaction and collaboration between the physical and life sciences communities has been one of the key strengths of the project
The main aim has been to provide a vision for the future of research in cognitive systems, both for the design of artificial cognitive systems (applications) and to further our scientific understanding of biological systems
The biologically-inspired approach focuses on the scientific study and, where appropriate, exploitation of naturally-occurring cognitive systems
The pure engineering approach seeks to create artificial systems that exhibit some desired level of cognitive performance or behaviour
Can we achieve more by combining the biologically inspired approach with the mathematical models of the engineering approach?
Overview
Speech & language (Grand Challenge) 3-D vision (Grand Challenge) How brains wire themselves (Keynote lecture) Brain rhythms (Grand Challenge) Memory & forgetting (Debate) Framework for the future?
Not covered here but some very important themes to emerge in discussion
Robotics Agents Learning Levels of analysis
Not covered here but some very important themes to emerge in discussion
Robotics Agents Learning Levels of analysis and emergent
properties Sensor fusion Affective cognition
To understand and emulate human capabilityfor robust communication and interaction.
To understand and emulate human capabilityfor robust communication and interaction.
Grand Challenge Language and speech
To construct a neuro-biologically realistic, computationally specific account of human language processing.
To construct functionally accurate models of human interaction based on and consistent with real-world data.
To build and demonstrate human-computer interfaces which demonstrate human levels of robustness and flexibility.
Goals:
10Grand Challenge
0
5
10
15
20
25
30
35
40
SpeakerIndependentDictationBroadcastNews
TelephoneConversations
11
Progress in Automatic Speech Recognition
State of the Art: Speech Recognition
Easy
Hard
Wor
d E
rror
Rat
e
What Humans Do that Today’s Systems Don’t
Use context to interpret and respond to questions Ask for clarification Relate new information to what’s already been said Avoid repetition Use linguistic and prosodic cues to convey meaning
Distinguish what’s new or interesting Signal misunderstanding, lack of agreement, rejection
Adapt to their conversational partners Manage the conversational turn Learn from experience
12State of the Art: Computational Language Systems
700 ms720 ms740 ms750 ms760 ms770 ms780 ms790 ms800 ms
13State of the Art: Cognitive Neuroscience of Speech and Language
Demonstration using MEG to track cortical activity related to spoken word recognition
Demonstration using MEG to track cortical activity related to spoken word recognition
1. Greater scientific understanding of human cognition and communication
2. Significant advances in noise-robust speech recognition, understanding, and generation technology
3. Dialogue systems capable of adapting to their users and learning on-line
4. Improved treatment and rehabilitation of disorders in language function; novel language prostheses
Summary of Benefits
To understand and emulate human capabilityfor robust communication and interaction.
To understand and emulate human capabilityfor robust communication and interaction.
14Grand Challenge
Grand Challenge - 3D Vision
Measurements
3D Structure using computational geometry
A 3D Visual Task
Biological systems can perform 3D tasks using visual information
Pointing to remembered objects Ants homing
Real-time 3D localisation in natural scenes using the engineering approach will not be possible simply as a result of increase in computational power
“computer vision hitting a computational wall” The design of a biologically plausible model of 3D
localisation is a Grand Challenge which would take us through the wall
Overview
Speech & language (Grand Challenge) 3-D vision (Grand Challenge) How brains wire themselves (Keynote lecture)
How brains wire themselves
(Keynote lecture – Mriganka Sur)
Specificity
Plasticity
Optic tract
Lateralgeniculate
n.Optic
radiations
Primaryvisualcortex
The visual cortex has specific processing networks
Orientation selectivity in V1: How do orientation networks form?
D.H. Hubel T.N. Wiesel
Optical imaging of cortical activity
Cortical vasculature
Single orientation images Composite orientation map
Light guide
Stimuluscomputer
Video dataacquisition
Ca
me
ra
Amplifier
Normal
Rewired
Visually responsive auditory cortex
MGN
LGN
Visual cortex
Auditory cortex
Visual cortex
SuperiorcolliculusLGN
Inferior colliculi
MGN
Rewiring alters the pattern of activity to the developing cortex
M. Sur and C. Leamey, Nature Reviews Neurosci, 2001
J. Sharma, A. Angelucci, M. Sur, Nature, 2000
Orientation maps arise in rewired A1
How brains wire themselves
Specificity
Plasticity
Some aspects of
arise by virtue of
Implications : should engineering systems incorporate self-organisation and, if so, how?
Brain rhythms (Grand Challenge)
How are representations of perceptual events given the correct temporal organisation for storage and recall?
The rhythmic activities of different groups of neurons in the brain may play a fundamental role in helping us to do this.
Computer scientists working in the area of asynchronous
computing are interested in any insight into how complex asynchronous natural systems can deliver coherent behaviours
Hypothesis is that each period of the fast gamma rhythm underlies a specific representation.
Gamma is superimposed on a slower rhythm (alpha or theta) that effectively multiplexes the representations
This mechanism could explain how the interactions between neuronal rhythms participate in shaping the holding in short-term (working) memory of perceptual events: the fast wave representations would constitute the contents of each discrete snapshot, the entire percept being mediated by the slow waves.
Gamma-theta interaction
From VanRullen & Koch, 2003
Memory and Forgetting (Debate)
• New “intelligent” information processing software should take more account of advances in our growing understanding of human memory systems.
But should they compensate for, or mimic their known failings, including forgetting?
Synaptic potentiation shows varying persistence
Memory also fails for psychological reasons….
The “seven sins” of memory The sin of transience The sin of absent-
mindedness The sin of blocking The sin of misattribution The sin of suggestibility
The sin of bias The sin of persistence
Weakening or loss Breakdown of attention Thwarted memory
search Assigning to wrong
source Implanted by a leading
question Editing and rewriting Repeated recall of
disturbing informationAfter Schacter (2001)After Schacter (2001)
The “seven sins” of memory (Dan Schacter)
• Schacter argues that they are not really “failures” at all, but reflect the proper operation of a finely tuned system…. not vices but virtues.
• Should we build into artificial devices for storing and retrieving information the same “trade-offs” between memory and forgetting that we see in human systems?
Overview
Speech & language (Grand Challenge) 3-D vision (Grand Challenge) How brains wire themselves (Keynote lecture) Brain rhythms (Grand Challenge) Memory & forgetting (Debate) Framework for the future?
Framework for the Future
In the study of “cognitive systems”, can the interaction between life and physical sciences be better promoted by setting up an appropriate infrastructure?
Critical mass of scientists
Technology and instrumentation
Dedicated research programs
Relevant training programs
If yes….
Momentum generated by this Foresight Project must be maintained
The following might be fruitful areas of interaction: 3D-Vision for natural scenes Speech and language – natural dialogue Memory systems Action and robotics Social cognition
Other topics also offer important and tractable problems.
Possible research themes (not an exhaustive list)
How do humans recognise objects? How could the new paradigm of generative models help us
to understand sensory processing in mammalian brains? The use of context in both artificial and natural systems Can appreciation of the social context of speech get us
beyond the apparent limits of machine-learning? How does the brain encode and remember time? How are we to understand intentionality in action? What are the principles and functional consequences of
self-organisation?