IGEM:IMPERIAL/2008/Projects/Wall-E.coli

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WALL-E.COLI HAS BEEN SCRAPPED

R.I.P WALL-E...

Creation of modular upgrades to 'E.coli' to produce autonomous intelligent agent functionality will have wide uses in science in industry. With E.coli more able to survive in a greater range of environments, being able to decide what it needs to do to improvce its survival chance.

Contents

Autonomous Intelligent Agents

To quote a Coneural report

'The three–constituents principle

Designing autonomous agents always involves three constituents: (1) definition of the ecological niche, (2) definition of desired behaviors and tasks, and (3) the design of the agent (Pfeifer & Scheier, 1999, pp. 302–306). The range of environments that agents may inhabit can exhibit a lot of variety. No single agent can adapt, both physically and cognitively, to cope economically with all the possible variations. Biological agents, animals or plants, are also limited in their adaptability to a specific environmental niche. A desired ecological niche must thus be established, prior to the design of the agents. Given the specific niche, the desired behaviors or tasks to be solved can be specified, and then the agent may be designed according to these needs. In some cases, the physical design of the agent is given (for example, if the robot is bought off-the-shelf), and only the control system can be designed, 12 given the desired behaviors. In other cases, there might be a given agent architecture and the research will consist in the exploration of the emerging behaviors in a particular ecological niche. The three constituents are interdependent: the design critically depends on the desired behaviors and the niche, the possible behaviors are dependent on the environment and the agent, and the ecological niche where the agent is viable depends on its structure and on what it does.'[1]

Simply, to design an autonomous agent you need to know 1) the environment in which it will reside (in this case the environment of the E.coli, 2) the behaviour or function of the device required and then to take into account the design itself, as in what type of agent does it have to be (simple, capable of learning etc.)

The lysogenic function of some viruses could be compared in a way as an autonomous agent as they 'sense' the environment, in particular the 'health' of the bacterium they have invaded and respond to it in reference to what it should be to provide a stable home by either integrating themselves into the genome or replicating and lysing the cell.They do this so as to carry own their agenda - in this case their replication and survival.

Wikipedia discusses the different ways of understanding agent intelligence in computer systems, with 2 differing deffinitions which work in different ways; ending in a distinction between intelligent agents and autonomous agents.[2]

An intelligent agent is one that adapts and responds to the environment on the behalf of a user. An autonomous agent is one that works on its own behalf to achieve its goals.

For our E.coli, both deffinitions occur symultaneously, as it can be used by us as a factory or transfer function while also trying to stay alive by whatever means, making our E.coli an intelligent agent and an autonomous agent. As such, our E.coli ia an intelligent autonomous agent.

The core of our project is to improve E.coli and the simplest way is by 'programming' simple genetic systems that function as intelligent agents as they will carry out a process for us by increasing the efficiency and survival chance of the cell. In particular this will require using biological components as part of the computer system architecture

Environment Modifications

  1. Modifying the Environment

Differentiation versus Common culture versus Parallel circuitry

What is the best way to engineer a biological system?

Differentiation

Common Culture

Parallel Circuitry

Application - Heavy Metal Water Filter

  1. Background on the causes and problems of heavy ion pollution
  2. Information on potential promoters and metal binding proteins
  3. Implementation


  1. Coneural [1]
  2. Wikipedia page on Intelligent agents

    [2]

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