System and method for conscious machines

A computational method for interacting with a physical environment, comprising:

• receiving information relating to a robotic self agent, other agents, and objects in the physical environment;
• establishing at least one goal based on at least a set of rules for interacting between the robotic self agent and the other agents and objects in the physical environment;
• periodically updating a simplified dynamical predictive model of the physical environment which provides a coherent narrative of the robotic self agent interacting with the other agents and the objects in the physical environment, based on at least the received information, and storing a series of the simplified dynamical predictive models with at least one automated processor;
• predicting a plurality of alternative future states of the robotic self agent, the other agents, and the objects within the physical environment with a causal model with the at least one automated processor;
• deciding between prospective alternate actions of the robotic self agent with the at least one automated processor, based on at least the at least one goal, the stored simplified dynamical predictive models, and the plurality of alternative future states;
• and
• controlling the robotic self agent to interact with the other agents and the objects in the physical environment, dependent on at least the prospective alternate actions of the robotic self agent, by producing an output for changing a relationship of at least one of the robotic self agent, the other agents, and the objects in the physical environment.

A method for controlling interactions of a robotic agent within a physical environment, comprising:

• defining a set of rules for interacting between the robotic agent and the physical environment;
• recognizing active other agents in the physical environment, objects in the physical environment, and the robotic agent in the physical environment;
• recognizing changes in the physical environment using pattern recognition based on an environmental status input;
• sequentially generating and storing a series of simplified dynamical predictive models of the physical environment comprising other agents, the robotic agent, and the objects;
• defining at least one goal for the robotic agent based on at least the set of rules;
• making alternative predictions of future states of the other agents, the robotic agent, and objects within the physical environment using a simplified dynamical predictive model, based on alternate different actions by the robotic agent and past representations stored in the memory with at least one automated processor;
• generating decisions based on the goals and the alternate predictions with the at least one automated processor;
• controlling the robotic agent, the agents in the physical environment, and the objects in the physical environment, dependent on the generated decisions, to change a relationship;
• and
• updating the simplified dynamical predictive model to present a dynamic narrative of the robotic agent within the physical environment.