Steering T-Cell Adaptation Using Opponent Exploitation Algorithms and Computational Game Theory (Research Area 10.3)

Abstract

The objective of the project is to develop techniques for algorithmically computing sequential contingent plans for steering a T cell population to the kind of T cell population that is needed against the disease at hand (cancers versus autoimmune disease versus infections). The objective of the biological experiment portion of this project is to further develop both experimental and mathematical tools to allow for testing of novel strategies suggested by the algorithms developed in this project.

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Document Details

Document Type
Technical Report
Publication Date
Sep 17, 2021
Accession Number
AD1204293

Entities

People

  • Tuomas Sandholm

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Autoimmune Diseases
  • Cell Physiological Processes
  • Cells
  • Computational Science
  • Computer Science
  • Computers
  • Control Systems
  • Diseases
  • Extensive-Form Games
  • Game Theory
  • Information Processing
  • Information Science
  • Information Systems
  • Lymphocytes
  • Machine Learning
  • Mathematical Models
  • Models
  • Multiagent Systems
  • Simulators
  • Zero-Sum Games

Fields of Study

  • Biology

Readers

  • Distributed Systems and Data Platform Development
  • Game Theory.
  • Immunology