257:
One of the advantages of forward-chaining over backward-chaining is that the reception of new data can trigger new inferences, which makes the engine better suited to dynamic situations in which conditions are likely to change.
273:: Expert systems are AI systems that mimic the decision-making abilities of human experts in a specific domain. They rely on forward chaining to apply expert knowledge to solve problems and make recommendations.
484:
279:: Forward chaining is extensively used in medical diagnosis and troubleshooting systems, where the input symptoms and test results are used to determine potential causes and treatments.
461:
266:
Forward chaining is a powerful reasoning strategy with numerous applications in AI and related fields. Some of the prominent applications include:
224:
The name "forward chaining" comes from the fact that the inference engine starts with the data and reasons its way to the answer, as opposed to
297:: In natural language processing, forward chaining can be applied to resolve ambiguities in language and extract useful information from text.
204:
1. Since the base facts indicate that "Fritz croaks" and "Fritz eats flies", the antecedent of rule #1 is satisfied by substituting Fritz for
491:
285:: Educational software often employs forward chaining to adapt to students’ progress and provide customized learning paths and feedback.
291:: Forward chaining is utilized in business and management decision support systems to analyze data and recommend actions or strategies.
190:
Let us illustrate forward chaining by following the pattern of a computer as it evaluates the rules. Assume the following facts:
500:
56:
109:
Suppose that the goal is to conclude the color of a pet named Fritz, given that he croaks and eats flies, and that the
768:
388:
359:
19:
This article is about forward chaining inference engines. For forward chaining as an instructional procedure, see
758:
228:, which works the other way around. In the derivation, the rules are used in the opposite order as compared to
593:
405:
748:
664:
578:
477:
644:
621:
573:
827:
791:
601:
312:
705:
201:
With forward reasoning, the inference engine can derive that Fritz is green in a series of steps:
822:
735:
317:
786:
743:
720:
700:
606:
82:
clause) is known to be true. When such a rule is found, the engine can conclude, or infer, the
669:
550:
535:
525:
52:
351:
801:
781:
611:
520:
415:. Krakow, Poland: Institute of Automatics: AGH University of Science and Technology, Poland
8:
583:
504:
469:
236:
34:
690:
75:
796:
753:
725:
636:
616:
515:
384:
377:
355:
307:
243:
235:
Because the data determines which rules are selected and used, this method is called
232:. In this example, rules #2 and #4 were not used in determining that Fritz is green.
229:
225:
60:
540:
344:
71:
38:
776:
545:
74:
using forward chaining searches the inference rules until it finds one where the
70:
to extract more data (from an end user, for example) until a goal is reached. An
322:
98:
67:
816:
560:
247:
240:
48:
434:
43:
626:
214:
2. The antecedent of rule #3 is then satisfied by substituting Fritz for
91:
83:
374:
110:
403:
20:
710:
654:
404:
Kaczor, Krzystof; Szymon Bobek; Grzegorz J. Nalepa (2010-12-05).
685:
375:
Hayes-Roth, Frederick; Donald
Waterman; Douglas Lenat (1983).
246:
inference. The forward chaining approach is often employed by
715:
695:
659:
568:
251:
47:. Forward chaining is a popular implementation strategy for
649:
499:
462:
Forward vs. Backward
Chaining Explained at SemanticWeb.com
41:
and can be described logically as repeated application of
66:
Forward chaining starts with the available data and uses
376:
343:
814:
368:
101:through this process until a goal is reached.
485:
492:
478:
341:
90:clause), resulting in the addition of new
815:
218:, and the inference engine concludes:
208:, and the inference engine concludes:
59:. The opposite of forward chaining is
473:
33:) is one of the two main methods of
16:Inference engine in an expert system
113:contains the following four rules:
13:
435:"Applications of Forward Chaining"
406:"Overview of Expert System Shells"
14:
839:
455:
261:
427:
397:
346:The Rise of the Expert Company
335:
1:
328:
277:Diagnosis and Troubleshooting
749:Constraint logic programming
665:Knowledge Interchange Format
622:Procedural reasoning systems
579:Expert systems for mortgages
574:Connectionist expert systems
283:Intelligent Tutoring Systems
7:
645:Attempto Controlled English
342:Feigenbaum, Edward (1988).
301:
295:Natural Language Processing
10:
844:
104:
18:
792:Preference-based planning
767:
734:
678:
635:
592:
559:
511:
313:Constraint Handling Rules
501:Knowledge representation
289:Decision Support Systems
736:Constraint satisfaction
379:Building Expert Systems
350:. Times Books. p.
318:Opportunistic reasoning
97:Inference engines will
57:production rule systems
787:Partial-order planning
744:Constraint programming
670:Web Ontology Language
612:Deductive classifiers
551:Knowledge engineering
536:Model-based reasoning
526:Commonsense reasoning
802:State space planning
782:Multi-agent planning
584:Legal expert systems
521:Case-based reasoning
769:Automated planning
637:Ontology languages
607:Constraint solvers
383:. Addison-Wesley.
828:Logic programming
810:
809:
797:Reactive planning
754:Local consistency
594:Reasoning systems
541:Inference engines
516:Backward chaining
413:geist.agh.edu.pl/
308:Backward chaining
244:backward chaining
239:, in contrast to
230:backward chaining
226:backward chaining
61:backward chaining
31:forward reasoning
835:
546:Proof assistants
531:Forward chaining
494:
487:
480:
471:
470:
449:
448:
446:
445:
431:
425:
424:
422:
420:
410:
401:
395:
394:
382:
372:
366:
365:
349:
339:
211:Fritz is a frog
197:Fritz eats flies
72:inference engine
39:inference engine
27:Forward chaining
843:
842:
838:
837:
836:
834:
833:
832:
813:
812:
811:
806:
777:Motion planning
763:
730:
679:Theorem provers
674:
631:
602:Theorem provers
588:
555:
507:
498:
467:
458:
453:
452:
443:
441:
433:
432:
428:
418:
416:
408:
402:
398:
391:
373:
369:
362:
340:
336:
331:
304:
264:
222:
221:Fritz is green
212:
107:
94:to its data.
68:inference rules
24:
17:
12:
11:
5:
841:
831:
830:
825:
823:Expert systems
808:
807:
805:
804:
799:
794:
789:
784:
779:
773:
771:
765:
764:
762:
761:
756:
751:
746:
740:
738:
732:
731:
729:
728:
723:
718:
713:
708:
703:
698:
693:
688:
682:
680:
676:
675:
673:
672:
667:
662:
657:
652:
647:
641:
639:
633:
632:
630:
629:
624:
619:
617:Logic programs
614:
609:
604:
598:
596:
590:
589:
587:
586:
581:
576:
571:
565:
563:
561:Expert systems
557:
556:
554:
553:
548:
543:
538:
533:
528:
523:
518:
512:
509:
508:
497:
496:
489:
482:
474:
465:
464:
457:
456:External links
454:
451:
450:
439:www.doubtly.in
426:
396:
389:
367:
360:
333:
332:
330:
327:
326:
325:
323:Rete algorithm
320:
315:
310:
303:
300:
299:
298:
292:
286:
280:
274:
271:Expert Systems
263:
260:
248:expert systems
220:
210:
199:
198:
195:
188:
187:
179:is a canary -
171:
155:
135:
106:
103:
49:expert systems
37:when using an
15:
9:
6:
4:
3:
2:
840:
829:
826:
824:
821:
820:
818:
803:
800:
798:
795:
793:
790:
788:
785:
783:
780:
778:
775:
774:
772:
770:
766:
760:
757:
755:
752:
750:
747:
745:
742:
741:
739:
737:
733:
727:
724:
722:
719:
717:
714:
712:
709:
707:
704:
702:
699:
697:
694:
692:
689:
687:
684:
683:
681:
677:
671:
668:
666:
663:
661:
658:
656:
653:
651:
648:
646:
643:
642:
640:
638:
634:
628:
625:
623:
620:
618:
615:
613:
610:
608:
605:
603:
600:
599:
597:
595:
591:
585:
582:
580:
577:
575:
572:
570:
567:
566:
564:
562:
558:
552:
549:
547:
544:
542:
539:
537:
534:
532:
529:
527:
524:
522:
519:
517:
514:
513:
510:
506:
502:
495:
490:
488:
483:
481:
476:
475:
472:
468:
463:
460:
459:
440:
436:
430:
414:
407:
400:
392:
390:0-201-10686-8
386:
381:
380:
371:
363:
361:0-8129-1731-6
357:
353:
348:
347:
338:
334:
324:
321:
319:
316:
314:
311:
309:
306:
305:
296:
293:
290:
287:
284:
281:
278:
275:
272:
269:
268:
267:
259:
255:
253:
249:
245:
242:
238:
233:
231:
227:
219:
217:
209:
207:
202:
196:
193:
192:
191:
185:
182:
178:
175:
172:
169:
166:
162:
159:
156:
153:
150:
146:
142:
139:
136:
133:
130:
127:eats flies -
126:
122:
119:
116:
115:
114:
112:
102:
100:
95:
93:
89:
85:
81:
77:
73:
69:
64:
62:
58:
54:
50:
46:
45:
40:
36:
32:
28:
22:
627:Rule engines
530:
466:
442:. Retrieved
438:
429:
417:. Retrieved
412:
399:
378:
370:
345:
337:
294:
288:
282:
276:
270:
265:
262:Applications
256:
234:
223:
215:
213:
205:
203:
200:
194:Fritz croaks
189:
183:
180:
176:
173:
167:
164:
163:is a frog -
160:
157:
151:
148:
144:
140:
137:
131:
128:
124:
120:
117:
108:
96:
87:
79:
65:
44:modus ponens
42:
30:
26:
25:
759:SMT solvers
241:goal-driven
237:data-driven
154:is a canary
143:chirps and
123:croaks and
92:information
817:Categories
444:2023-11-02
419:5 December
329:References
250:, such as
84:consequent
76:antecedent
505:reasoning
134:is a frog
111:rule base
35:reasoning
302:See also
170:is green
147:sings -
53:business
21:Chaining
711:Prover9
706:Paradox
655:F-logic
186:is blue
105:Example
99:iterate
686:CARINE
387:
358:
716:SPASS
701:Otter
696:Nqthm
660:FO(.)
569:CLIPS
409:(PDF)
252:CLIPS
650:CycL
503:and
421:2013
385:ISBN
356:ISBN
181:Then
165:Then
149:Then
129:Then
88:Then
55:and
29:(or
721:TPS
352:318
819::
726:Z3
437:.
411:.
354:.
254:.
174:If
158:If
138:If
118:If
80:If
63:.
51:,
691:E
493:e
486:t
479:v
447:.
423:.
393:.
364:.
216:X
206:X
184:X
177:X
168:X
161:X
152:X
145:X
141:X
132:X
125:X
121:X
86:(
78:(
23:.
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.