TESIS DOCTORAL - Robotics Lab - Universidad Carlos III de Madrid

More documents

Recommendations

Info

2.4 Emotions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242.4.1 The role of emotions . . . . . . . . . . . . . . . . . . . . . . . . . 242.4.2 What is an emotion? . . . . . . . . . . . . . . . . . . . . . . . . . 252.4.3 Theories about emotions . . . . . . . . . . . . . . . . . . . . . . . 262.4.4 Emotion systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 272.4.5 The Appraisal Theory . . . . . . . . . . . . . . . . . . . . . . . . 292.4.6 Emotional reactions . . . . . . . . . . . . . . . . . . . . . . . . . 312.4.7 Fear, anxiety and the amygdala . . . . . . . . . . . . . . . . . . . . 332.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 State of the Art 373.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.2 Social Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.2.1 Social robots for research . . . . . . . . . . . . . . . . . . . . . . . 393.2.2 Social robots for entertainment . . . . . . . . . . . . . . . . . . . . 403.2.3 Therapeutic social robots . . . . . . . . . . . . . . . . . . . . . . . 413.2.4 Social robots for assistance . . . . . . . . . . . . . . . . . . . . . . 423.3 Control Architectures based on motivations and emotions . . . . . . . . . . 443.3.1 The Cathexis architecture (Velásquez, 1997) . . . . . . . . . . . . . 453.3.2 Cañamero’s approach (1997) . . . . . . . . . . . . . . . . . . . . . 473.3.3 The ALEC architecture (Gadanho, 1998) . . . . . . . . . . . . . . 493.3.4 Breazeal’s model (2000) . . . . . . . . . . . . . . . . . . . . . . . 503.3.5 Other works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523.3.6 Comparative analysis . . . . . . . . . . . . . . . . . . . . . . . . . 623.3.7 Why do robots need emotions? . . . . . . . . . . . . . . . . . . . . 653.3.8 Differences with the followed approach . . . . . . . . . . . . . . . 663.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 674 The Decision Making System 694.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 694.2 A motivational decision making system for a social robot . . . . . . . . . . 694.3 Learning in the DMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 724.3.1 Reinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . 724.3.2 The robot’s wellbeing . . . . . . . . . . . . . . . . . . . . . . . . 764.4 Considered emotions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 784.4.1 Happiness/sadness . . . . . . . . . . . . . . . . . . . . . . . . . . 794.4.2 Fear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 814.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85x
5 The social robot Maggie and its decision making system 875.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 875.2 The robot Maggie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 875.3 The Automatic-Deliberative control architecture . . . . . . . . . . . . . . . 895.3.1 Deliberative level . . . . . . . . . . . . . . . . . . . . . . . . . . . 905.3.2 Automatic level . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905.3.3 AD Communications . . . . . . . . . . . . . . . . . . . . . . . . . 915.3.4 AD Skill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 915.4 Featuring Maggie’s DMS . . . . . . . . . . . . . . . . . . . . . . . . . . . 925.4.1 The robot’s inner world: what drives and motivations? . . . . . . . 935.4.2 The external world: sensing and acting . . . . . . . . . . . . . . . 995.4.3 Acting in the world: what to do next? . . . . . . . . . . . . . . . . 1045.4.4 The consequences of the robot’s actions . . . . . . . . . . . . . . . 1065.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1076 Learning to make decisions 1096.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1096.2 Object Q-Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1096.2.1 The state space . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1106.2.2 Reduced state space . . . . . . . . . . . . . . . . . . . . . . . . . 1116.2.3 Collateral effects and Object-Q learning . . . . . . . . . . . . . . . 1136.2.4 The algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1146.3 Enhancing the learning process . . . . . . . . . . . . . . . . . . . . . . . . 1226.3.1 Well-balanced Exploration . . . . . . . . . . . . . . . . . . . . . . 1226.3.2 Amplified Reward . . . . . . . . . . . . . . . . . . . . . . . . . . 1246.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1257 Implementing the decision making system 1277.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1277.2 Decision Making System database design . . . . . . . . . . . . . . . . . . 1287.3 Decision Making System class design . . . . . . . . . . . . . . . . . . . . 1337.3.1 The external robot’s world class design . . . . . . . . . . . . . . . 1367.3.2 The inner robot’s world class diagram . . . . . . . . . . . . . . . . 1387.4 How the external state is perceived . . . . . . . . . . . . . . . . . . . . . . 1417.4.1 The location monitor . . . . . . . . . . . . . . . . . . . . . . . . . 1437.4.2 The music player sensor . . . . . . . . . . . . . . . . . . . . . . . 1457.4.3 The docking station sensor . . . . . . . . . . . . . . . . . . . . . . 1457.4.4 The bluetooth discoverer . . . . . . . . . . . . . . . . . . . . . . . 1467.4.5 The rfid discoverer . . . . . . . . . . . . . . . . . . . . . . . . . . 1497.5 How the robot interacts with the objects . . . . . . . . . . . . . . . . . . . 151xi
Page 1: TESIS DOCTORALBIO-INSPIRED DECISION
Page 7 and 8: AgradecimientosSon muchas las veces
Page 9 and 10: AbstractRobotics is an emergent fie
Page 11 and 12: ResumenLa robótica es un área eme
Page 13: ContentsAgradecimientosAbstractResu
Page 18 and 19: 9.4 Harm/interactions with Alvaro d
Page 20 and 21: 3.10 An overview of the net of syst
Page 23: List of Algorithms6.1 Object Q-Lear
Page 26 and 27: xxii
Page 28 and 29: 2 Chapter 1. IntroductionFigure 1.1
Page 30 and 31: 4 Chapter 1. Introductionautonomous
Page 32 and 33: 6 Chapter 1. IntroductionAs in othe
Page 34 and 35: 8 Chapter 1. Introductiondesired ou
Page 36 and 37: 10 Chapter 1. Introduction1.4 Overv
Page 38 and 39: 12 Chapter 1. Introduction
Page 40 and 41: 14 Chapter 2. Biological foundation
Page 64 and 65:
38 Chapter 3. State of the Artand b
Page 66 and 67:
40 Chapter 3. State of the Art(a) R
Page 68 and 69:
42 Chapter 3. State of the Artpatie
Page 70 and 71:
44 Chapter 3. State of the Art(a) i
Page 72 and 73:
46 Chapter 3. State of the Artrange
Page 74 and 75:
48 Chapter 3. State of the Artwell
Page 76 and 77:
50 Chapter 3. State of the Artthe a
Page 78 and 79:
52 Chapter 3. State of the ArtThe e
Page 80 and 81:
54 Chapter 3. State of the Arttask.
Page 82 and 83:
56 Chapter 3. State of the Artthe r
Page 84 and 85:
58 Chapter 3. State of the Artit is
Page 86 and 87:
60 Chapter 3. State of the Artthe r
Page 88 and 89:
62 Chapter 3. State of the Artnon-l
Page 90 and 91:
64 Chapter 3. State of the ArtTAME
Page 92 and 93:
66 Chapter 3. State of the ArtMinsk
Page 94 and 95:
68 Chapter 3. State of the Art
Page 96 and 97:
70 Chapter 4. The Decision Making S
Page 98 and 99:
Page 100 and 101:
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
Page 114 and 115:
88 Chapter 5. The social robot Magg
Page 116 and 117:
Page 118 and 119:
Page 120 and 121:
Page 122 and 123:
Page 124 and 125:
Page 126 and 127:
100 Chapter 5. The social robot Mag
Page 128 and 129:
Page 130 and 131:
Page 132 and 133:
Page 134 and 135:
Page 136 and 137:
110 Chapter 6. Learning to make dec
Page 138 and 139:
Page 140 and 141:
Page 142 and 143:
Page 144 and 145:
Page 146 and 147:
Page 148 and 149:
Page 150 and 151:
Page 152 and 153:
Page 154 and 155:
128 Chapter 7. Implementing the dec
Page 156 and 157:
Page 158 and 159:
Page 160 and 161:
Page 162 and 163:
Page 164 and 165:
Page 166 and 167:
Page 168 and 169:
Page 170 and 171:
Page 172 and 173:
Page 174 and 175:
Page 176 and 177:
Page 178 and 179:
Page 180 and 181:
Page 182 and 183:
Page 184 and 185:
Page 186 and 187:
Page 188 and 189:
Page 190 and 191:
Page 192 and 193:
166 Chapter 8. Testing the experime
Page 194 and 195:
Page 196 and 197:
Page 198 and 199:
Page 200 and 201:
Page 202 and 203:
Page 204 and 205:
178 Chapter 9. Experimental Results
Page 206 and 207:
Page 208 and 209:
Page 210 and 211:
Page 212 and 213:
Page 214 and 215:
Page 216 and 217:
Page 218 and 219:
Page 220 and 221:
Page 222 and 223:
Page 224 and 225:
198 Chapter 10. Conclusions and Fut
Page 226 and 227:
Page 228 and 229:
Page 230 and 231:
Page 232 and 233:
Page 234 and 235:
208 Bibliography[8] M. A. Martínez
Page 236 and 237:
210 Bibliography[35] B. Hardy-Vall
Page 238 and 239:
212 Bibliography[63] J. LeDoux, “
Page 240 and 241:
214 Bibliography[90] C. Bartneck an
Page 242 and 243:
216 Bibliography[115] B. Graf, U. R
Page 244 and 245:
218 Bibliography[140] W. P. Lee, J.
Page 246 and 247:
220 Bibliography[166] C. Isbell, C.
Page 248 and 249:
222 Bibliography[190] M. A. Salichs
show all

TESIS DOCTORAL - Robotics Lab - Universidad Carlos III de Madrid

Create successful ePaper yourself

Delete template?

Save as template?