Integrative biological simulation praxis: Considerations from physics, philosophy, and data/model curation practices

We describe a biologically-inspired research agenda with parallel tracks aimed at AI and AI safety. The bottom-up component consists of building a sequence of biophysically realistic simulations of simple organisms such as the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the zebrafish Danio rerio to serve as platforms for research into AI algorithms and system architectures. The top-down component consists of an approach to value alignment that grounds AI goal structures in neuropsychology, broadly considered. Our belief is that parallel pursuit of these tracks will inform the development of value-aligned AI systems that have been inspired by embodied organisms with sensorimotor integration. An important set of side benefits is that the research trajectories we describe here are grounded in long-standing intellectual traditions within existing research communities and funding structures. In addition, these research programs overlap with significant contemporary themes in the biological and psychological sciences such as data/model integration and reproducibility.

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Integrative biological simulation, neuropsychology, and AI safety

10.7287/peerj.preprints.27321 ◽

2019 ◽

Author(s):

Gopal P Sarma ◽

Adam Safron ◽

Nick J. Hay

Keyword(s):

Data Model ◽

Research Agenda ◽

Sensorimotor Integration ◽

Fruit Fly ◽

Biologically Inspired ◽

Goal Structures ◽

System Architectures ◽

Intellectual Traditions ◽

Biological Simulation ◽

Ai Safety

We describe a biologically-inspired research agenda with parallel tracks aimed at AI and AI safety. The bottom-up component consists of building a sequence of biophysically realistic simulations of simple organisms such as the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the zebrafish Danio rerio to serve as platforms for research into AI algorithms and system architectures. The top-down component consists of an approach to value alignment that grounds AI goal structures in neuropsychology, broadly considered. Our belief is that parallel pursuit of these tracks will inform the development of value-aligned AI systems that have been inspired by embodied organisms with sensorimotor integration. An important set of side benefits is that the research trajectories we describe here are grounded in long-standing intellectual traditions within existing research communities and funding structures. In addition, these research programs overlap with significant contemporary themes in the biological and psychological sciences such as data/model integration and reproducibility.

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Integrative biological simulation, neuropsychology, and AI safety

10.7287/peerj.preprints.27321v2 ◽

2019 ◽

Author(s):

Gopal P Sarma ◽

Adam Safron ◽

Nick J. Hay

Keyword(s):

Data Model ◽

Research Agenda ◽

Sensorimotor Integration ◽

Fruit Fly ◽

Biologically Inspired ◽

Goal Structures ◽

System Architectures ◽

Intellectual Traditions ◽

Biological Simulation ◽

Ai Safety

We describe a biologically-inspired research agenda with parallel tracks aimed at AI and AI safety. The bottom-up component consists of building a sequence of biophysically realistic simulations of simple organisms such as the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the zebrafish Danio rerio to serve as platforms for research into AI algorithms and system architectures. The top-down component consists of an approach to value alignment that grounds AI goal structures in neuropsychology, broadly considered. Our belief is that parallel pursuit of these tracks will inform the development of value-aligned AI systems that have been inspired by embodied organisms with sensorimotor integration. An important set of side benefits is that the research trajectories we describe here are grounded in long-standing intellectual traditions within existing research communities and funding structures. In addition, these research programs overlap with significant contemporary themes in the biological and psychological sciences such as data/model integration and reproducibility.

Download Full-text

Integrative biological simulation, neuropsychology, and AI safety

10.7287/peerj.preprints.27321v1 ◽

2018 ◽

Author(s):

Gopal P Sarma ◽

Adam Safron ◽

Nick J. Hay

Keyword(s):

Data Model ◽

Research Agenda ◽

Sensorimotor Integration ◽

Fruit Fly ◽

Biologically Inspired ◽

Goal Structures ◽

System Architectures ◽

Intellectual Traditions ◽

Biological Simulation ◽

Ai Safety

We propose a biologically-inspired research agenda with parallel tracks aimed at AI and AI safety. The bottom-up component consists of building a sequence of biophysically realistic simulations of simple organisms such as the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the zebrafish Danio rerio to serve as platforms for research into AI algorithms and system architectures. The top-down component consists of an approach to value alignment that grounds AI goal structures in neuropsychology. Our belief is that parallel pursuit of these tracks will inform the development of value-aligned AI systems that have been inspired by embodied organisms with sensorimotor integration. An important set of side benefits is that the research trajectories we describe here are grounded in long-standing intellectual traditions within existing research communities and funding structures. In addition, these research programs overlap with significant contemporary themes in the biological and psychological sciences such as data/model integration and reproducibility.

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Decision Making in Team Sports: Data, model and applied perspective

PsycEXTRA Dataset ◽

10.1037/e509992008-001 ◽

2008 ◽

Author(s):

Pedro J. M. Passos ◽

Duarte Araujo ◽

Keith Davids ◽

Ana Diniz ◽

Luis Gouveia ◽

...

Keyword(s):

Decision Making ◽

Data Model ◽

Team Sports ◽

Sports Data

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A Qualified Assertion Database for the History of Places

International Journal of Humanities and Arts Computing ◽

10.3366/ijhac.2019.0233 ◽

2019 ◽

Vol 13 (1-2) ◽

pp. 95-115

Author(s):

Brandon Plewe

Keyword(s):

Data Model ◽

Temporal Change ◽

Religious Congregations ◽

Historical Gis ◽

The Past ◽

Model Based ◽

Complex Information ◽

Invaluable Tool ◽

History Of ◽

The Rich

Historical place databases can be an invaluable tool for capturing the rich meaning of past places. However, this richness presents obstacles to success: the daunting need to simultaneously represent complex information such as temporal change, uncertainty, relationships, and thorough sourcing has been an obstacle to historical GIS in the past. The Qualified Assertion Model developed in this paper can represent a variety of historical complexities using a single, simple, flexible data model based on a) documenting assertions of the past world rather than claiming to know the exact truth, and b) qualifying the scope, provenance, quality, and syntactics of those assertions. This model was successfully implemented in a production-strength historical gazetteer of religious congregations, demonstrating its effectiveness and some challenges.

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