An Optimal Itinerary Generation in a Configuration Space of Large Intellectual Agent Groups with Linear Logic

11/06/2018
by   Dmitry Maximov, et al.
0

A group of intelligent agents which fulfill a set of tasks in parallel is represented first by the tensor multiplication of corresponding processes in a linear logic game category. An optimal itinerary in the configuration space of the group states is defined as a play with maximal total reward in the category. New moments also are: the reward is represented as a degree of certainty (visibility) of an agent goal, and the system goals are chosen by the greatest value corresponding to these processes in the system goal lattice.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/27/2018

Game Semantics and Linear Logic in the Cognition Process

A description of the environment cognition process by intelligent system...
research
04/24/2019

Grounding Natural Language Commands to StarCraft II Game States for Narration-Guided Reinforcement Learning

While deep reinforcement learning techniques have led to agents that are...
research
10/31/2019

A Narration-based Reward Shaping Approach using Grounded Natural Language Commands

While deep reinforcement learning techniques have led to agents that are...
research
04/27/2023

Categorification of Group Equivariant Neural Networks

We present a novel application of category theory for deep learning. We ...
research
04/13/2021

Group Recommendation Techniques for Feature Modeling and Configuration

In large-scale feature models, feature modeling and configuration proces...
research
04/07/2019

Network Models from Petri Nets with Catalysts

Petri networks and network models are two frameworks for the composition...

Please sign up or login with your details

Forgot password? Click here to reset