System and methods for immunocomputing applied to collectives of nanorobots

• US 20080270097A1
• Filed: 11/13/2007
• Published: 10/30/2008
• Est. Priority Date: 11/13/2006
• Status: Abandoned Application

• Current Assignee: Solomon Research LLC
• Original Assignee: Solomon Research LLC
• Inventors: Solomon, Neal
• Application Number:
  US11/985,074
• Publication Number:
  US 20080270097A1
• Time in Patent Office: Days
• US Class Current: 703/11
• CPC Class Codes: A61B 5/416 the spleen
• CPC Class Codes: A61M 37/00 Other apparatus for introducing media into the body for reproduction or fertilisation A61B17/425; apparatus for iontophoresis or cataphoresis A61N1/30; Percutany, i.e. introducing medicines into the body by diffusion through the skin salt baths A61H33/04
• CPC Class Codes: B82Y 10/00 Nanotechnology for information processing, storage or transmission, e.g. quantum computing or single electron logic
• CPC Class Codes: G06N 3/002 Biomolecular computers, i.e. using biomolecules, proteins, cells using DNA G06N3/123; using neurons G06N3/061
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

The invention describes immunocomputing methods for application to collectives of nanorobots (CNRs). The system provides a hybrid synthesis of adaptive immune system problem solving and anticipatory problem solving in the CNR environment. Modeling methods are advanced to guide the transformation process of CNRs in the context of evolvable hardware, including a time-series modeling approach.

Claims

1. A system for anticipatory immunocomputing, comprising:

a computer system, including memory, for processing data;

a database management system;

an intelligent mobile software agent (IMSA) system for accessing a database and exchanging data;

wherein the computer system develops computer models to simulate the trajectories of the evolution of artificial antigens;

wherein the computer modeling develops calculations of the rate of change of the mutations of the antigens'"'"' evolutionary vectors;

wherein the computer modeling anticipates the evolutionary vector scenarios of the artificial antigens;

wherein data about the immunocomputing anticipatory model is forwarded to a collective of nanorobots (CNR) system using IMSAs; and

wherein the CNR develops specific behaviors to self-organize.

2. A system for hybrid immunocomputing, comprising:

A computer system, including memory, for processing data;

A database management system;

An intelligent mobile software agent (IMSA) system for accessing a database and exchanging data;

Wherein the computer system develops humoral immune system models to apply existing solutions of optimization problems;

Wherein the computer system develops adaptive immune system models to develop solutions for novel combinatorial optimization problems;

Wherein the computer system develops computer models to anticipate the evolution of artificial antigens to solve optimization problems;

Wherein the humoral, adaptive and anticipatory immune system models are integrated into a hybrid immunocomputing model to provide solutions to and apply solutions involving optimization problems;

Wherein a new artificial antigen presents an optimization problem;

Wherein the hybrid immunocomputing model is forwarded to a collective of nanorobots (CNRs) by using IMSAs; and

Wherein the CNR performs specific self-organizing behaviors by adapting its configuration to implement a solution to an optimization problem.

3. A system for managing a distributed computer network, comprising;

A computer system, including memory, for processing data;

A database management system;

An intelligent mobile software agent (IMSA) system for accessing a database and exchanging data;

A collective of nanorobotics with computational capabilities;

Wherein the computer system develops a model of the CNR system;

Wherein the computer model uses three dimensional cellular automata simulations to model the CNR;

Wherein the computer system develop a model of the indeterministic CNR environment;

Wherein the CNR system is comprised of a distributed computer network;

Wherein computer models of the environment are integrated into a model of the CNR system;

Wherein as the environment changes the computer model modeling the environment changes;

Wherein the computer models are sent to the CNR by IMSAs;

Wherein the CNR receives the data on the computer models and changes its geometric configuration;

Wherein the CNR changes its geometric configuration in response to the changes in the environment; and

Wherein the computer modeling is used to make course corrections of the CNRs as the environment changes and as the strategic objectives change.