INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM

• US 20100318478A1
• Filed: 06/01/2010
• Published: 12/16/2010
• Est. Priority Date: 06/11/2009
• Status: Abandoned Application

• Current Assignee: Sony Corporation (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.)
• Inventors: Sabe, Kohtaro, Noda, Kuniaki, Kawamoto, Kenta, Yoshiike, Yukiko
• Application Number:
  US12/791,240
• Publication Number:
  US 20100318478A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06F 18/295 Markov models or related models, e.g. semi-Markov models; Markov random fields; Networks embedding Markov models
• CPC Class Codes: G06N 3/006 based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16

Abstract

An information processing device includes: a calculating unit configured to calculate a current-state series candidate that is a state series for an agent capable of actions reaching the current state, based on a state transition probability model obtained by performing learning of the state transition probability model stipulated by a state transition probability that a state will be transitioned according to each of actions performed by an agent capable of actions, and an observation probability that a predetermined observation value will be observed from the state, using an action performed by the agent, and an observation value observed at the agent when the agent performs an action; and a determining unit configured to determine an action to be performed next by the agent using the current-state series candidate in accordance with a predetermined strategy.

Claims

1. An information processing device comprising:

calculating means configured to calculate a current-state series candidate that is a state series for an agent capable of actions reaching the current state, based on a state transition probability model obtained by

performing learning of said state transition probability model stipulated by

a state transition probability that a state will be transitioned according to each of actions performed by an agent capable of actions, and

an observation probability that a predetermined observation value will be observed from said state,

using

an action performed by said agent, and

an observation value observed at said agent when said agent performs an action; and

determining means configured to determine an action to be performed next by said agent using said current-state series candidate in accordance with a predetermined strategy.

2. The information processing device according to claim 1, wherein said determining means determine an action in accordance with a strategy for increasing information of an unknown situation not obtained at said state transition probability model.

3. The information processing device according to claim 2, wherein said calculating means estimate, with an action series of actions performed by said agent, and an observation value series of observation values observed at said agent when said actions are performed as an action series for recognition for recognizing the situation of an agent, and an observation value series, one or more state series for recognition that are state series wherein state transition occurs in which said action series for recognition and said observation value series are observed, and select one or more candidates of said current-state series out of one or more of said state series for recognition;

and wherein said determining means detect an action of which the state transition probability of state transition from a final state that is the final state of said current-state series candidate to an immediate before state that is a state immediately before said final state is the maximum as a return action wherein state transition for returning the state to said immediate before state regarding each of one or more candidates of said current-state series, obtain the sum of the state transition probabilities of state transitions with said final state as the transition source for each action as an action suitability degree representing suitability for performing the action thereof regarding each of one or more candidates of said current-state series, obtain an action other than said return action of actions of which said action suitability degree is equal to or greater than a predetermined threshold, as an action candidate to be performed next regarding each of one or more candidates of said current-state series, and determine an action to be performed next out of said action candidates to be performed next.

4. The information processing device according to claim 1, wherein said determining means determine an action in accordance with a strategy for increasing information whereby the situation of said agent is recognizable.

5. The information processing device according to claim 4, wherein said calculating means estimate, with an action series of actions performed by said agent, and an observation value series of observation values observed at said agent when said actions are performed as an action series for recognition for recognizing the situation of an agent, and an observation value series, one or more state series for recognition that are state series wherein state transition occurs in which said action series for recognition and said observation value series are observed, and select one or more candidates of said current-state series out of one or more of said state series for recognition;

and wherein said determining means detect an action of which the state transition probability of state transition from a final state that is the final state of said current-state series candidate to an immediate before state that is a state immediately before said final state is the maximum as an action to be performed next regarding each of one or more candidates of said current-state series, and determine an action to be performed next out of said action candidates to be performed next.

6. The information processing device according to claim 1, wherein said determining means determine an action in accordance with a strategy for performing an action performed by said agent in a known situation similar to the current situation of said agent of known situations obtained at said state transition probability model.

7. The information processing device according to claim 6, wherein said calculating means estimate, with an action series of actions performed by said agent, and an observation value series of observation values observed at said agent when said actions are performed as an action series for recognition for recognizing the situation of an agent, and an observation value series, one or more state series for recognition that are state series wherein state transition occurs in which said action series for recognition and said observation value series are observed, and select one or more candidates of said current-state series out of one or more of said state series for recognition;

and wherein said determining means obtain the sum of the state transition probabilities of state transitions with a final state that is the final state of said current-state series candidate as the transition source for each action as an action suitability degree representing suitability for performing the action thereof regarding each of one or more candidates of said current-state series, obtain an action of which said action suitability degree is equal to or greater than a predetermined threshold, as an action candidate to be performed next regarding each of one or more candidates of said current-state series, and determine an action to be performed next out of said action candidates to be performed next.

8. The information processing device according to claim 1, wherein said determining means select a strategy for determining an action out of a plurality of strategies, and determine an action in accordance with the strategy thereof.

9. The information processing device according to claim 8, wherein said determining means select a strategy for determining an action out of a strategy for increasing information of an unknown situation not obtained at said state transition probability model, and a strategy for increasing information whereby the situation of said agent is recognizable.

10. The information processing device according to claim 9, wherein said determining means select a strategy based on elapsed time since an unknown situation not obtained at said state transition probability model.

11. The information processing device according to claim 9, wherein said determining means select a strategy based on the time of a known situation obtained at said state transition probability model, or the percentage of an unknown situation not obtained at said state transition probability model, of imminent predetermined time.

12. The information processing device according to claim 1, wherein said calculating means repeat to estimate, with an action series of actions performed by said agent, and an observation value series of observation values observed at said agent when said actions are performed as an action series for recognition for recognizing the situation of an agent, and an observation value series, a most likely state series that is a state series where state transition occurs in which likelihood for said action series for recognition, and said observation value series being observed is the highest, and to determine whether the situation of said agent is a known situation obtained at said state transition probability model, or an unknown situation not obtained at said state transition probability model based on said most likely state series while increasing the series lengths of said action series for recognition and said observation value series until determination is made that the situation of said agent is said unknown situation, estimate one or more of state series for recognition that are state series where state transition occurs in which said action series for recognition and said observation value series, of which the series lengths are shorter than said series lengths at the time of determination being made that the situation of said agent is said unknown situation by one sample worth are observed, and select one or more candidates of said current state series out of said one or more state series for recognition;

and wherein said determining means determine an action using one or more candidates of said current state series.

13. An information processing method comprising the steps of:

calculating of a current-state series candidate that is a state series for an agent capable of actions reaching the current state, based on a state transition probability model obtained by

performing learning of said state transition probability model stipulated by

a state transition probability that a state will be transitioned according to each of actions performed by an agent capable of actions, and

an observation probability that a predetermined observation value will be observed from said state,

using

an action performed by said agent, and

an observation value observed at said agent when said agent performs an action; and

determining an action to be performed next by said agent using said current-state series candidate in accordance with a predetermined strategy.

14. A program causing a computer serving as:

calculating means configured to calculate a current-state series candidate that is a state series for an agent capable of actions reaching the current state, based on a state transition probability model obtained by

performing learning of said state transition probability model stipulated by

a state transition probability that a state will be transitioned according to each of actions performed by an agent capable of actions, and

an observation probability that a predetermined observation value will be observed from said state,

using

an action performed by said agent, and

an observation value observed at said agent when said agent performs an action; and

determining means configured to determine an action to be performed next by said agent using said current-state series candidate in accordance with a predetermined strategy.

15. An information processing device comprising:

a calculating unit configured to calculate a current-state series candidate that is a state series for an agent capable of actions reaching the current state, based on a state transition probability model obtained by

performing learning of said state transition probability model stipulated by

a state transition probability that a state will be transitioned according to each of actions performed by an agent capable of actions, and

an observation probability that a predetermined observation value will be observed from said state,

using

an action performed by said agent, and

an observation value observed at said agent when said agent performs an action; and

a determining unit configured to determine an action to be performed next by said agent using said current-state series candidate in accordance with a predetermined strategy.

16. A program causing a computer serving as:

a calculating unit configured to calculate a current-state series candidate that is a state series for an agent capable of actions reaching the current state, based on a state transition probability model obtained by

performing learning of said state transition probability model stipulated by

a state transition probability that a state will be transitioned according to each of actions performed by an agent capable of actions, and

an observation probability that a predetermined observation value will be observed from said state,

using

an action performed by said agent, and

an observation value observed at said agent when said agent performs an action; and

a determining unit configured to determine an action to be performed next by said agent using said current-state series candidate in accordance with a predetermined strategy.