What team members can learn from software agents
Human agents - learning from advances in distributed computing
I am delighted to republish a bioteams guest essay on “Agents: Technology and Usage” by James Odell which is attached in full as a pdf.
James was an early innovator of Information Engineering methodologies and more recently has been working with the OMG (Object Management Group) where he co-chaired their Agents Work Group.
He also worked extensively in the area of agent-based communication methods many of which are based on the messaging techniques of the social insects.
One of the central tenets of bioteams is to encourage team members to seek the many benefits of operating as responsible but autonomous team players.
This is the style of natures' best teams where rather than receiving direction through command and control leadership structures the members operate to varying degrees as self-managed agents.
One of the areas which has had the biggest success in applying biological principles is Distributed Computing where the concept of an ”agent” is a key element.
An agent can be a person, machine or a piece of software and is simply defined as “one who acts”.
In previous articles I have speculated on the most useful traits for bioteam members.
I believe James’ article is particularly useful in this context as it not only clarifies the agent concept but also shows how software agents communicate and interact with each other and their environments in real life applications.
The paper also defines some of the most important properties of agents such as:
- Autonomous
- Interactive
- Adaptive
- Sociable
- Mobile
- Proxy
- Proactive
- Intelligent
- Rational
- Unpredictable
- Credible
- Transparent
- Cooperative
- Competitive
- Rugged
- Trustworthy
Many if not all of these characteristics can be applied equally well to high-performing human teams.
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Complex adaptive systems and virtual team collaboration
Leading complexity thinkers apply biological principles to enterprises: The Biology of Business is a set of essays by ten researchers and practitioners in Complex Adaptive Systems (CAS).
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