Environment adaptive control of pseudo-emotion generating machine by repeatedly updating and adjusting at least either of emotion generation and behavior decision algorithms

• US 6,629,242 B2
• Filed: 12/13/2000
• Issued: 09/30/2003
• Est. Priority Date: 04/11/1997
• Status: Expired due to Fees

• Current Assignee: Yamaha Hatsudoki Kabushiki Kaisha (Yamaha Corporation)
• Original Assignee: Yamaha Hatsudoki Kabushiki Kaisha (Yamaha Corporation)
• Inventors: Kamiya, Tsuyoshi, Sakaue, Masaya
• Primary Examiner(s): Lee, Thomas
• Assistant Examiner(s): Wang, Albert
• Application Number:
  US09/736,514
• Publication Number:
  US 20010001318A1
• Time in Patent Office: 1,021 Days
• Field of Search: 345/863, 446/491, 706/11, 706/14, 706/23, 700/31, 700/47, 713/100
• US Class Current: 713/100
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 2110/10 Temperature
• CPC Class Codes: F24F 2110/12 of the outside air
• CPC Class Codes: F24F 2110/20 Humidity
• CPC Class Codes: F24F 2110/22 of the outside air
• CPC Class Codes: F24F 2110/32 of the outside air
• CPC Class Codes: F24F 2110/50 Air quality properties
• CPC Class Codes: F24F 2120/10 Occupancy
• CPC Class Codes: F24F 2120/20 Feedback from users
• CPC Class Codes: G06N 3/008 based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour
• CPC Class Codes: Y02B 30/70 Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating

Abstract

A control method for controlling operation of an object used by a user in an environment includes the steps of: defining pseudo-emotions of the object for deciding output of the object, in relation to the user'"'"'s state; formulating emotion generation algorithms to establish the relationship between the user'"'"'s state and the pseudo-emotions; formulating behavior decision algorithms to establish the relationship between input, including the pseudo-emotions, and the behavior of the object; detecting the user'"'"'s state; generating a pseudo-emotion of the object based on the user'"'"'s state using the emotion generation algorithms; making the object behave based on the user'"'"'s state and the pseudo-emotion using the behavior decision algorithms; evaluating reaction of the user in response to the behavior of the object; and if the reaction of the user does not match the pseudo-emotion of the object in the emotion generation algorithms, adjusting at least either of the emotion generation algorithms or the behavior decision algorithms, followed by learning the adjustment. The object can detect the user'"'"'s state in a visual, tactile, and auditory manner as do humans, and can act upon generation of pseudo-emotions based thereon. Thus, natural communication between the user and the object can be performed, i.e., more human like communication can be established.

Claims

1. A control method for controlling operation of a machine responsively to an environment of use, said machine being capable of receiving signals from the use environment and being programmed to behave in response to the received signals, said machine comprising:

(i) emotion generation algorithms formulated to establish the relationship between the signals and pseudo-emotions, said pseudo-emotions being defined as elements for deciding output of the machine, in relation to the signals; and

(ii) behavior decision algorithms formulated to establish the relationship between input, including the pseudo-emotions, and the behavior of the machine;

said method comprising the steps of;

(a) detecting signals from the environment of use and inputting the signals into the machine;

(b) generating a pseudo-emotion of the machine based on the signals using the emotion generation algorithms;

(c) making the machine behave based on the signals and the pseudo-emotion using the behavior decision algorithms;

(d) assessing changes, if any, in the environment of use in response to the behavior of the machine;

(e) if the changes in the environment of use do not match the pseudo-emotion of the machine in the emotion generation algorithms, adjusting and updating at least either of the emotion generation algorithms or the behavior decision algorithms, followed by learning the adjustment; and

(f) repeating steps (a) through (e).

2. The method according to claim 1, wherein the relationship between the signals and pseudo-emotions establised in the emotion generation algorithms is regulated by paramters, and adjusting the emotion generation algorithms in step (e) is changing the parameters.

3. The method according to claim 1, further comprising after step (a) a step of moving in a direction from which signals come if the intensity of the signals changes.

4. The method according to claim 1, wherein the machine receives signals from an external information source.