An experimental virtual platform for numerical experiments of computational models.
An engineering offer.
Context :
The computational models studied in computational neuroscience have applications that extend far beyond what is possible to experiment yet in human or non-human primate subjects. Real robotics experimentatios are also impaired by rather heavy technological constraints; for instance, it is not easy to dismantle a given embedded system in the course of emerging ideas.
The only versatile environment in which such complex behaviors can be studied both globally and at the level of details of the available modeling is a virtual environment, as in video games. Such a system can be implemented as «brainy-bot» (a programmed player based on our knowledge of the brain architecture) which goal is to survive in a complete manipulable environment. Up to our best knowledge, though several teams have used video games environment to stimulate a subject to study cerebral functions addressed here, nobody has “reversed” the experiment and attempted to falsify existing formalism by studying to which extent such behavioral brain models can help a brainy-bot to survive in such a virtual universe.
Work plan :
In order to attain this rather ambitious objective we are going to both (i) deploy an existing open-source video game middleware in order to be able to shape the survival situation to be studied and (ii) revisit the existing models in order to be able to integrate them as an effective brainy-bot.
The former technological development will consist of a platform associated to a scenario that would be the closest possible to a survival situation (foraging, predator-prey relationship, partner approach to reproduction) and in which it would be easy to integrate an artificial agent with sensory inputs (visual, touch and smell), emotional and somatosensory cues (hunger, thirst, fear, ..) and motor outputs (movement, gesture, ..) connected to a “brain” whose architecture will correspond to the major anatomical regions involved in the issues of learning and action selection (cortex areas detailed here, basal ganglia, hippocampus, and areas dedicated to sensorimotor processes). The internal game clock will be slowed down enough to be able to run non trivial brainy-bot implementations.
Context :
The computational models studied in computational neuroscience have applications that extend far beyond what is possible to experiment yet in human or non-human primate subjects. Real robotics experimentatios are also impaired by rather heavy technological constraints; for instance, it is not easy to dismantle a given embedded system in the course of emerging ideas.
The only versatile environment in which such complex behaviors can be studied both globally and at the level of details of the available modeling is a virtual environment, as in video games. Such a system can be implemented as «brainy-bot» (a programmed player based on our knowledge of the brain architecture) which goal is to survive in a complete manipulable environment. Up to our best knowledge, though several teams have used video games environment to stimulate a subject to study cerebral functions addressed here, nobody has “reversed” the experiment and attempted to falsify existing formalism by studying to which extent such behavioral brain models can help a brainy-bot to survive in such a virtual universe.
Work plan :
In order to attain this rather ambitious objective we are going to both (i) deploy an existing open-source video game middleware in order to be able to shape the survival situation to be studied and (ii) revisit the existing models in order to be able to integrate them as an effective brainy-bot.
The former technological development will consist of a platform associated to a scenario that would be the closest possible to a survival situation (foraging, predator-prey relationship, partner approach to reproduction) and in which it would be easy to integrate an artificial agent with sensory inputs (visual, touch and smell), emotional and somatosensory cues (hunger, thirst, fear, ..) and motor outputs (movement, gesture, ..) connected to a “brain” whose architecture will correspond to the major anatomical regions involved in the issues of learning and action selection (cortex areas detailed here, basal ganglia, hippocampus, and areas dedicated to sensorimotor processes). The internal game clock will be slowed down enough to be able to run non trivial brainy-bot implementations.
Then, efficient non-biological algorithms that the required input/output constraints are going to be integrated for each part of this distributed algorithmic system. The internal part of the brain modeling will directly relate on the «emergent» framework implementation (either used as it, or re-integrated in this specific environment). At this stage, the resulting brainy-bot is expected to exhibit a perennial survival in the virtual environment. This numerical experiment is a non-trivial way to attempt to falsify the proposed models. Its performances are going to be easily compared to a human or monkey performance (though not during the same run, since for obvious computational load the “brainy-bot” experiments require “slow down game clock”), or studied as such both qualitatively and quantitatively.
Then, efficient non-biological algorithms that the required input/output constraints are going to be integrated for each part of this distributed algorithmic system. The internal part of the brain modeling will directly relate on the «emergent» framework implementation (either used as it, or re-integrated in this specific environment). At this stage, the resulting brainy-bot is expected to exhibit a perennial survival in the virtual environment. This numerical experiment is a non-trivial way to attempt to falsify the proposed models. Its performances are going to be easily compared to a human or monkey performance (though not during the same run, since for obvious computational load the “brainy-bot” experiments require “slow down game clock”), or studied as such both qualitatively and quantitatively.
