Knowledge (XXG)

Witsenhausen's counterexample

Source đź“ť

1155:) has obtained slightly improved costs for the same parameter choice. The best known numerical results for a variety of parameters, including the one mentioned previously, are obtained by a local search algorithm proposed by S.-H. Tseng and A. Tang in 2017. The first provably approximately optimal strategies appeared in 2010 (Grover, Park, Sahai) where 1041:
The problem is of conceptual significance in decentralized control because it shows that it is important for the controllers to communicate with each other implicitly in order to minimize the cost. This suggests that control actions in decentralized control may have a dual role: those of control and
1063:
in the problem. However, this result requires the channels to be perfect and instantaneous, and hence is of limited applicability. In practical situations, the channel is always imperfect, and thus one can not assume that decentralized control problems are simple in presence of external channels.
46:
systems—that in a system with linear dynamics, Gaussian disturbance, and quadratic cost, affine (linear) control laws are optimal—to decentralized systems. Witsenhausen constructed a two-stage linear quadratic Gaussian system where two decisions are made by decision makers with decentralized
1037:
community. The importance of the problem was reflected upon in the 47th IEEE Conference on Decision and Control (CDC) 2008, Cancun, Mexico, where an entire session was dedicated to understanding the counterexample 40 years after it was first formulated.
1054:
show that the hardness is also because of the structure of the performance index and the coupling of different decision variables. It has also been shown that problems of the spirit of Witsenhausen's counterexample become simpler if the
62:
The statement of the counterexample is simple: two controllers attempt to control the system by attempting to bring the state close to zero in exactly two time steps. The first controller observes the initial state
748: 1137: 1016:
a non-optimal nonlinear solution for the control laws is given which gives a lower value for the expected cost function than does the best linear pair of control laws (Theorem 2).
47:
information and showed that for this system, there exist nonlinear control laws that outperform all linear laws. The problem of finding the optimal control law remains unsolved.
415: 358: 470: 218: 1050:
The hardness of the problem is attributed to the fact that information of the second controller depends on the decisions of the first controller. Variations considered by
837: 794: 894: 561: 91: 994: 957: 927: 666: 591: 299: 272: 245: 172: 145: 118: 1014: 929:
has a Gaussian distribution and if at least one of the controllers is constrained to be linear, then it is optimal for both controllers to be linear (Lemma 13).
635: 611: 247:
after the first controller's input. The second controller cannot communicate with the first controller and thus cannot observe either the original state
43: 753:
that give at least as good a value of the objective function as do any other pair of control functions. Witsenhausen showed that the optimal functions
52: 677: 1159:
is used to understand the communication in the counterexample. The optimal solution of the counterexample is still an open problem.
614: 1087:
A number of numerical attempts have been made to solve the counterexample. Focusing on a particular choice of problem parameters
1243:
Rotkowitz, M.; Cogill, R.; Lall, S.; "A Simple Condition for the Convexity of Optimal Control over Networks with Delays,"
1293:
Lee, Lau, and Ho. "The Witsenhausen counterexample: A hierarchical search approach for nonconvex optimization problems."
1034: 1359: 1280:
Baglietto, Parisini, and Zoppoli. "Numerical solutions to the Witsenhausen counterexample by approximating networks."
24: 1067:
A justification of the failure of attempts that discretize the problem came from the computer science literature:
1306:
Li, Marden, and Shamma. "Learning approaches to the Witsenhausen counterexample from a view of potential games."
1090: 1354: 1033:. Due to its hardness, the problem of finding the optimal control law has also received attention from the 899:
The exact solution is given for the case in which both controllers are constrained to be linear (Lemma 11).
1260: 1068: 963: 960: 364: 307: 426: 638: 177: 799: 756: 1156: 1056: 1030: 27: 857: 485: 1060: 31: 66: 51: 972: 935: 905: 644: 569: 277: 250: 223: 150: 123: 96: 1264: 1144: 1072: 1152: 1140: 1026: 999: 620: 596: 35: 1348: 476: 1319:
Tseng and Tang. "A Local Search Algorithm for the Witsenhausen's Counterexample."
1076: 1051: 20: 1332:
Grover, Sahai, and Park. "The finite-dimensional Witsenhausen counterexample."
39: 1230:
Basar, Tamer. "Variations on the theme of the Witsenhausen counterexample".
1148: 1059:
along an external channel that connects the controllers is smaller than the
1204:
Mitterrand and Sahai. "Information and Control: Witsenhausen revisited".
996:
has a Gaussian distribution, for some values of the preference parameter
566:
where the expectation is taken over the randomness in the initial state
174:
of the second controller is free, but it is based on noisy observations
1175:
Witsenhausen, Hans. "A counterexample in stochastic optimum control."
1193:
Proceedings of the 47th IEEE Conference on Decision and Control (CDC)
1249:
European Control Conference. CDC-ECC '05. 44th IEEE Conference on
932:
The exact nonlinear control laws are given for the case in which
743:{\displaystyle u_{1}(x_{0})\quad {\text{and}}\quad u_{2}(y_{1})} 1217:
Ho, Yu-Chi. "Team decision theory and information structures".
854:
The optimal control law of the first controller is such that
668:
differs depending on the particular version of the problem.
1075:
showed that the discrete version of the counterexample is
641:
manner, while the distribution of the initial state value
301:
of the first controller. Thus the system dynamics are
1093: 1002: 975: 938: 908: 860: 802: 759: 680: 647: 623: 599: 572: 488: 429: 367: 310: 280: 253: 226: 180: 153: 126: 99: 69: 19:, shown in the figure below, is a deceptively simple 147:
after the input of the second controller. The input
42:
that one can generalize a key result of centralized
1232:
47th IEEE Conference on Decision and Control Cancun
1191:Ho, Yu-Chi, "Review of the Witsenhausen problem". 1131: 1008: 988: 951: 921: 888: 831: 788: 742: 660: 629: 605: 585: 555: 464: 420:with the second controller's observation equation 409: 352: 293: 266: 239: 212: 166: 139: 112: 85: 120:of the first controller, and a cost on the state 1179:, Volume 6, Issue 1, pp. 131–147 (February 1968) 1025:The counterexample lies at the intersection of 1267:. "Intractable problems in control theory." 847:Witsenhausen obtained the following results: 8: 1269:24th IEEE Conference on Decision and Control 1139:, researchers have obtained strategies by 1109: 1147:. Further research (notably, the work of 1114: 1092: 1001: 980: 974: 943: 937: 913: 907: 871: 859: 820: 807: 801: 777: 764: 758: 731: 718: 708: 698: 685: 679: 671:The problem is to find control functions 652: 646: 622: 598: 577: 571: 541: 536: 514: 509: 493: 487: 475:The objective is to minimize an expected 447: 434: 428: 398: 385: 372: 366: 341: 328: 315: 309: 285: 279: 258: 252: 231: 225: 198: 185: 179: 158: 152: 131: 125: 104: 98: 74: 68: 1321:IEEE Conference on Decision and Control 1308:IEEE Conference on Decision and Control 1168: 1132:{\displaystyle (k=0.2,\;\sigma _{0}=5)} 1295:IEEE Transactions on Automatic Control 1282:IEEE Transactions on Automatic Control 1251:, pp. 6686–6691, 12–15 December 2005. 7: 1206:Learning, control and hybrid systems 1187: 1185: 637:is assumed to be distributed in a 410:{\displaystyle x_{2}=x_{1}-u_{2},} 353:{\displaystyle x_{1}=x_{0}+u_{1},} 14: 1151:, and the work of Li, Marden and 44:linear–quadratic–Gaussian control 1334:IEEE WiOpt 2010, ConCom workshop 1083:Attempts at obtaining a solution 843:Specific results of Witsenhausen 50: 1021:The significance of the problem 713: 707: 58:Statement of the counterexample 1126: 1094: 877: 864: 851:An optimum exists (Theorem 1). 826: 813: 783: 770: 737: 724: 704: 691: 547: 529: 520: 502: 465:{\displaystyle y_{1}=x_{1}+z.} 1: 213:{\displaystyle y_{1}=x_{1}+z} 93:There is a cost on the input 17:Witsenhausen's counterexample 1035:theoretical computer science 832:{\displaystyle u_{2}(y_{1})} 789:{\displaystyle u_{1}(x_{0})} 1221:, Vol. 68, No.6, June 1980. 1046:The hardness of the problem 1376: 1234:, Mexico, Dec. 9–11, 2008. 889:{\displaystyle E(x_{1})=0} 593:and the observation noise 617:. The observation noise 556:{\displaystyle k^{2}E+E,} 613:, which are distributed 1219:Proceedings of the IEEE 30:. It was formulated by 1261:Christos Papadimitriou 1195:, pp. 1611–1613, 2008. 1133: 1069:Christos Papadimitriou 1010: 990: 964:symmetric distribution 953: 923: 890: 833: 790: 744: 662: 631: 607: 587: 557: 466: 411: 354: 295: 268: 241: 214: 168: 141: 114: 87: 86:{\displaystyle x_{0}.} 1134: 1011: 991: 989:{\displaystyle x_{0}} 954: 952:{\displaystyle x_{0}} 924: 922:{\displaystyle x_{0}} 891: 834: 791: 745: 663: 661:{\displaystyle x_{0}} 632: 608: 588: 586:{\displaystyle x_{0}} 558: 467: 412: 355: 296: 294:{\displaystyle u_{1}} 269: 267:{\displaystyle x_{0}} 242: 240:{\displaystyle x_{1}} 215: 169: 167:{\displaystyle u_{2}} 142: 140:{\displaystyle x_{2}} 115: 113:{\displaystyle u_{1}} 88: 1245:Decision and Control 1091: 1000: 973: 936: 906: 858: 800: 757: 678: 645: 621: 597: 570: 486: 427: 365: 308: 278: 251: 224: 178: 151: 124: 97: 67: 546: 519: 1360:Stochastic control 1157:information theory 1129: 1057:transmission delay 1031:information theory 1006: 986: 949: 919: 886: 839:cannot be linear. 829: 786: 740: 658: 627: 603: 583: 553: 532: 505: 462: 407: 350: 291: 264: 237: 210: 164: 137: 110: 83: 28:stochastic control 1208:, 1999, Springer. 1061:propagation delay 1009:{\displaystyle k} 711: 630:{\displaystyle z} 606:{\displaystyle z} 34:in 1968. It is a 32:Hans Witsenhausen 1367: 1337: 1330: 1324: 1317: 1311: 1304: 1298: 1291: 1285: 1278: 1272: 1258: 1252: 1247:, 2005 and 2005 1241: 1235: 1228: 1222: 1215: 1209: 1202: 1196: 1189: 1180: 1173: 1138: 1136: 1135: 1130: 1119: 1118: 1015: 1013: 1012: 1007: 995: 993: 992: 987: 985: 984: 958: 956: 955: 950: 948: 947: 928: 926: 925: 920: 918: 917: 895: 893: 892: 887: 876: 875: 838: 836: 835: 830: 825: 824: 812: 811: 795: 793: 792: 787: 782: 781: 769: 768: 749: 747: 746: 741: 736: 735: 723: 722: 712: 709: 703: 702: 690: 689: 667: 665: 664: 659: 657: 656: 636: 634: 633: 628: 612: 610: 609: 604: 592: 590: 589: 584: 582: 581: 562: 560: 559: 554: 545: 540: 518: 513: 498: 497: 471: 469: 468: 463: 452: 451: 439: 438: 416: 414: 413: 408: 403: 402: 390: 389: 377: 376: 359: 357: 356: 351: 346: 345: 333: 332: 320: 319: 300: 298: 297: 292: 290: 289: 273: 271: 270: 265: 263: 262: 246: 244: 243: 238: 236: 235: 219: 217: 216: 211: 203: 202: 190: 189: 173: 171: 170: 165: 163: 162: 146: 144: 143: 138: 136: 135: 119: 117: 116: 111: 109: 108: 92: 90: 89: 84: 79: 78: 54: 1375: 1374: 1370: 1369: 1368: 1366: 1365: 1364: 1345: 1344: 1341: 1340: 1336:, Seoul, Korea. 1331: 1327: 1318: 1314: 1305: 1301: 1292: 1288: 1279: 1275: 1265:John Tsitsiklis 1259: 1255: 1242: 1238: 1229: 1225: 1216: 1212: 1203: 1199: 1190: 1183: 1177:SIAM J. Control 1174: 1170: 1165: 1145:neural networks 1110: 1089: 1088: 1085: 1073:John Tsitsiklis 1048: 1042:communication. 1023: 998: 997: 976: 971: 970: 939: 934: 933: 909: 904: 903: 867: 856: 855: 845: 816: 803: 798: 797: 773: 760: 755: 754: 727: 714: 694: 681: 676: 675: 648: 643: 642: 619: 618: 595: 594: 573: 568: 567: 489: 484: 483: 443: 430: 425: 424: 394: 381: 368: 363: 362: 337: 324: 311: 306: 305: 281: 276: 275: 254: 249: 248: 227: 222: 221: 194: 181: 176: 175: 154: 149: 148: 127: 122: 121: 100: 95: 94: 70: 65: 64: 60: 12: 11: 5: 1373: 1371: 1363: 1362: 1357: 1355:Control theory 1347: 1346: 1339: 1338: 1325: 1312: 1299: 1286: 1273: 1253: 1236: 1223: 1210: 1197: 1181: 1167: 1166: 1164: 1161: 1141:discretization 1128: 1125: 1122: 1117: 1113: 1108: 1105: 1102: 1099: 1096: 1084: 1081: 1047: 1044: 1027:control theory 1022: 1019: 1018: 1017: 1005: 983: 979: 967: 946: 942: 930: 916: 912: 900: 897: 885: 882: 879: 874: 870: 866: 863: 852: 844: 841: 828: 823: 819: 815: 810: 806: 785: 780: 776: 772: 767: 763: 751: 750: 739: 734: 730: 726: 721: 717: 706: 701: 697: 693: 688: 684: 655: 651: 626: 602: 580: 576: 564: 563: 552: 549: 544: 539: 535: 531: 528: 525: 522: 517: 512: 508: 504: 501: 496: 492: 473: 472: 461: 458: 455: 450: 446: 442: 437: 433: 418: 417: 406: 401: 397: 393: 388: 384: 380: 375: 371: 360: 349: 344: 340: 336: 331: 327: 323: 318: 314: 288: 284: 261: 257: 234: 230: 209: 206: 201: 197: 193: 188: 184: 161: 157: 134: 130: 107: 103: 82: 77: 73: 59: 56: 36:counterexample 13: 10: 9: 6: 4: 3: 2: 1372: 1361: 1358: 1356: 1353: 1352: 1350: 1343: 1335: 1329: 1326: 1322: 1316: 1313: 1309: 1303: 1300: 1296: 1290: 1287: 1283: 1277: 1274: 1270: 1266: 1262: 1257: 1254: 1250: 1246: 1240: 1237: 1233: 1227: 1224: 1220: 1214: 1211: 1207: 1201: 1198: 1194: 1188: 1186: 1182: 1178: 1172: 1169: 1162: 1160: 1158: 1154: 1150: 1146: 1142: 1123: 1120: 1115: 1111: 1106: 1103: 1100: 1097: 1082: 1080: 1078: 1074: 1070: 1065: 1062: 1058: 1053: 1045: 1043: 1039: 1036: 1032: 1028: 1020: 1003: 981: 977: 968: 965: 962: 944: 940: 931: 914: 910: 901: 898: 883: 880: 872: 868: 861: 853: 850: 849: 848: 842: 840: 821: 817: 808: 804: 778: 774: 765: 761: 732: 728: 719: 715: 699: 695: 686: 682: 674: 673: 672: 669: 653: 649: 640: 624: 616: 615:independently 600: 578: 574: 550: 542: 537: 533: 526: 523: 515: 510: 506: 499: 494: 490: 482: 481: 480: 478: 477:cost function 459: 456: 453: 448: 444: 440: 435: 431: 423: 422: 421: 404: 399: 395: 391: 386: 382: 378: 373: 369: 361: 347: 342: 338: 334: 329: 325: 321: 316: 312: 304: 303: 302: 286: 282: 274:or the input 259: 255: 232: 228: 220:of the state 207: 204: 199: 195: 191: 186: 182: 159: 155: 132: 128: 105: 101: 80: 75: 71: 57: 55: 53: 48: 45: 41: 38:to a natural 37: 33: 29: 26: 25:decentralized 22: 18: 1342: 1333: 1328: 1320: 1315: 1307: 1302: 1294: 1289: 1281: 1276: 1268: 1256: 1248: 1244: 1239: 1231: 1226: 1218: 1213: 1205: 1200: 1192: 1176: 1171: 1086: 1066: 1049: 1040: 1024: 846: 752: 670: 565: 474: 419: 61: 49: 16: 15: 1077:NP-complete 1052:Tamer Basar 966:(Lemma 15). 21:toy problem 1349:Categories 1163:References 1143:and using 896:(Lemma 9). 40:conjecture 1149:Yu-Chi Ho 1112:σ 961:two-point 392:− 639:Gaussian 1323:, 2017. 1310:, 2009. 1284:. 2001. 1297:, 2001 1271:, 1985 1153:Shamma 959:has a 1263:and 1071:and 1029:and 796:and 1104:0.2 969:If 902:If 710:and 23:in 1351:: 1184:^ 1079:. 479:, 1127:) 1124:5 1121:= 1116:0 1107:, 1101:= 1098:k 1095:( 1004:k 982:0 978:x 945:0 941:x 915:0 911:x 884:0 881:= 878:) 873:1 869:x 865:( 862:E 827:) 822:1 818:y 814:( 809:2 805:u 784:) 779:0 775:x 771:( 766:1 762:u 738:) 733:1 729:y 725:( 720:2 716:u 705:) 700:0 696:x 692:( 687:1 683:u 654:0 650:x 625:z 601:z 579:0 575:x 551:, 548:] 543:2 538:2 534:x 530:[ 527:E 524:+ 521:] 516:2 511:1 507:u 503:[ 500:E 495:2 491:k 460:. 457:z 454:+ 449:1 445:x 441:= 436:1 432:y 405:, 400:2 396:u 387:1 383:x 379:= 374:2 370:x 348:, 343:1 339:u 335:+ 330:0 326:x 322:= 317:1 313:x 287:1 283:u 260:0 256:x 233:1 229:x 208:z 205:+ 200:1 196:x 192:= 187:1 183:y 160:2 156:u 133:2 129:x 106:1 102:u 81:. 76:0 72:x

Index

toy problem
decentralized
stochastic control
Hans Witsenhausen
counterexample
conjecture
linear–quadratic–Gaussian control

cost function
independently
Gaussian
two-point
symmetric distribution
control theory
information theory
theoretical computer science
Tamer Basar
transmission delay
propagation delay
Christos Papadimitriou
John Tsitsiklis
NP-complete
discretization
neural networks
Yu-Chi Ho
Shamma
information theory


Christos Papadimitriou

Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.

↑