An environment, to be truly smart, must learn from the cumulative data within its realm to understand and guess what likely choices might be for a given agent and then facilitate or enact these on behalf of that agent.
1. The first principle of Thing Theory is that the Thing-agent operates as a meta-agent over the entire technology context, not as a sub-component. Our Thing-agent assembles capabilities (e.g. whether or not the refrigerator light is suitable as a lamp) that are extensible based on what subcomponents of the system happen to be available. In short, what Thing can do is ultimately limited by the basic capabilities of various system subcomponents in combination with its knowledge about these and how to combine capabilities to make new more context sensitive capabilities.
2. The second principle of Thing Theory is that to increase the Thing-agent’s capabilities, more information from subcomponents must be shared.
3. The third principle of Thing Theory is that the Thing-agent must be context aware, and able to identify that different combinations of capabilities are available in different contexts, and has a corresponding capacity to manipulate contexts (e.g. enact, repress, aggregate) to ‘reveal’ new capabilities, many of which may be ‘innovations’ based on context discovery (invention).
4. The fourth principle of Thing Theory is that a Thing-agent extends the capabilities of other meta-agents. In order for the fourth principle to work, the meta-agents (a social network of at least one Thing-agent and another meta-gent) must have some type of transparency or at least shared permissions for exchange of capabilities and contexts. To describe or analyze such multi-agent systems, we must take into account the social as well as the individual behaviors of the agents.
Applin, S.A. and Fischer, M.D., Thing Theory: Connecting Humans to Location-Aware Smart Environments
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