公开(公告)号：US20230394413A1

公开(公告)日：2023-12-07

申请号：US18330930

申请日：2023-06-07

Applicant: SRI International

Inventor： Subhodev Das ,  Aswin Nadamuni Raghavan ,  Avraham Joshua Ziskind ,  Timothy J. Meo ,  Bhoram Lee ,  Chih-hung Yeh ,  John Cadigan ,  Ali Chaudhry ,  Jonathan C. Balloch

IPC: G06Q10/0637

CPC classification number: G06Q10/06375

Abstract: In general, the disclosure describes techniques for Artificial Intelligence (AI) models that can automatically generate diverse, explainable, interpretable, reactive, and coordinated behaviors for a team. In an example, a method includes receiving multimodal input data within a simulator configured to simulate solving a predefined problem by a team including a plurality of agents; generating one or more generative neural network models based on the multimodal input data and based on a predetermined threshold of success of problem solving in the simulator; outputting, by the one or more generative neural network models, one or more multi-agent controllers, wherein each of the one or more multi-agent controllers comprises recommended behaviors for each of the plurality of agents to solve the predefined problem in a manner that is consistent with the multimodal input data.

公开(公告)号：US20240265266A1

公开(公告)日：2024-08-08

申请号：US18434435

申请日：2024-02-06

Applicant: SRI International

Inventor： Theodore Camus ,  Zachary Seymour ,  Bhoram Lee ,  Andrew C. Silberfarb ,  Supun Samarasekera ,  Jonathan Brookshire

IPC: G06N3/092 ,  G06N3/042

CPC classification number: G06N3/092 ,  G06N3/042

Abstract: In general, techniques are described for coordinating actions of a plurality of agents or subsystems using a machine learning system that implements a Capability Graph Network (CGN). In an example, a method includes generating a control policy model comprising a plurality of nodes and a plurality of edges interconnecting the plurality of nodes, wherein the plurality of nodes represents a plurality of agents or subsystems and the plurality of edges represent information exchange between the plurality of agents or subsystems; and encoding agent behavior control policy within the control policy model for executing to coordinate a plurality of the actions of the plurality of agents or subsystems.