Semantic Reasoning for Natural and Seamless interactions between robots, humans and smart objects
In this case, we present a scenario, where assistive agents can collectively work together to solve ubiquitous problems. This scenario captures the milk dilemma and a possible solution where machines and sensors can assist in answering this daily issue. Let us consider when Eden goes to the grocery store, do she always remember to capture all the required food before departing. The answer is commonly, ”no”, as humans often forget to check many common items. For example, while at the store she don’t know the amount of milk available at home, a call can typically be made to someone at home (Steve) to query the status of milk. If there is no human at home to call the problem then falls to another actor in the system to answer the common query. Why not ask the refrigerator or the companion robot to determine this status? In this case, the task of determining the milk status is indistinguishable between another human, a robot or any other machine like the refrigerator. Which system actor answers the query of the milk status does not matter. The key point is the adequate capability present to answer the query.
In this scenario, let us assume that reasoning system of the refrigerator will notify the companion robot each time when a food (milk) is missing or if it becomes bad. When Eden approaches a grocery store, her smart phone will recognize the proximity to the grocery store an notifies the smart objects at home. The robot and the refrigerator will capture this notification and only the robot has the reasoning capability for dealing with that. It will decide to contact Eden asking her to buy the milk. We consider that Eden will accept and may ask if is there some yogurt. When the refrigerator and the robot reasoners fail in providing an answer by querying their local knowledge bases, the robot decides to ask the closest person “Steve” to get the missing information and forward the answer to Eden. Semantic reasoning, natural interactions and context awareness are the key concepts that makes the intelligence of actors. To further this innovation, the relationship between Humans, software Agents, Robots, Machines and Sensors (HARMS) must approach that of indistinguishability in multi agents systems communication. In fact, the whole concept of indistinguishability is novel and useful in terms of capability based organizations, where the system selects a task for execution, based on the capability of some agent (or other HARMS actor) given its capability to accomplish the selected task or solve a goal. All available actors with that specific capability allow the choice to be indistinguishable. Communication is the medium to enable indistinguishability, but is useful in an organization setting where group rational decisions and choices are made
References:
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N. Ayari, A. Chibani, and Y. Amirat, "Semantic Management of Human-Robot Interaction In Ambient Intelligence using N-ary ontologies," in ICRA 2013, Karlsruhe, Germany, May. 2013, pp. 1164-1171. .
N. Ayari, A. Chibani, and Y. Amirat, "A Semantic Approach to Enhance Human-Robot Interaction in AmI Environments," in Human-Agent Interaction, Workshop at IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012, Vilamoura, Portugal, 2012. .