clarke@csri.toronto.edu (Jim Clarke) (03/11/89)
ACTIVITIES FOR THE WEEK COMMENCING MARCH 27, 1989 (SF = Sandford Fleming Building, 10 King's College Road) (GB = Galbraith Building, 35 St. George Street) SUMMARY: COLLOQUIUM - Tues., March 28, 11 a.m. in Rm SF 1105 -- Donald Norman "Cognitive Artifacts, or, Things That Make Us Smart" NUMERICAL ANALYSIS SEMINAR - Tues., March 28, 11 a.m. in Rm GB 420 -- Paul Muir "Error Expressing for Reflected and Averaged Implicit Runge-Kutta Methods" NUMERICAL ANALYSIS SEMINAR - Fri., Mar. 31, 10 a.m. in Rm SF4102 -- Chris Fraley "Single-Phase vs. Multi-Phase Projective Methods for Linear Programming" -------------------- COLLOQUIUM - Tuesday, March 28, 11 a.m. in Room SF 1105 Donald Norman University of California, San Diego "Cognitive Artifacts, or, Things That Make Us Smart" The power of the unaided human mind is highly overrated. Ar- tifacts play a critical role in human performance, whether it be as an aid to memory, spatial reasoning, attentional focus, or communication. I give examples of the role that even simple ar- tifacts can play -- for spatial communication, reminders, pre- computation, task restructuring -- and present the beginnings of a theoretical analysis of the interaction between internal and external knowledge and structure. NUMERICAL ANALYSIS SEMINAR - Tuesday, March 28, 11:10 a.m. in Room GB 420 Paul Muir Saint Mary's University "Error Expressing for Reflected and Averaged Implicit Runge-Kutta Methods" In addition to their usefulness in the numerical solution of ini- tial value ODE's, the implicit Runge-Kutta (IRK) methods are also important for the solution of two-point boundary value problems. Recently, several classes of modified IRK methods which improve significantly on the efficiency of the standard IRK methods in this application have been presented. One such class is the Aver- aged IRK methods; a member of the class is obtained by applying an averaging operation to a non-symmetric IRK method and its re- flection. In this talk we investigate the forms of the error ex- pressions for reflected and averaged IRK methods. Our first result relates the expression for the local error of the reflect- ed method to that of the original method. Our main result relates the error expression of an averaged method to that of the method upon which it is based. We apply these results to show that for each member of the class of the averaged methods, there exists an embedded lower order method suitable for use in error estimation, in a formula-pair fashion. NUMERICAL ANALYSIS SEMINAR - Friday, March 31, 10 a.m. in Room SF 4102 Chris Fraley University of Geneva "Single-Phase vs. Multi-Phase Projective Methods for Linear Programming" This talk concerns a specific class of projective methods for linear programming. The methods in this class differ from most projective methods in that they never project onto the unit sim- plex, and they need not be started at a feasible point for the linear program. More than one algorithm can be devised within this framework. For example, it is possible to treat feasibility and optimality in entirely separate phases, or to approach feasi- bility and optimality simultaneously. We discuss several dif- ferent options, and give comparative performance results. We will also address some general computational issues related to projective methods for linear programming. -- Jim Clarke -- Dept. of Computer Science, Univ. of Toronto, Canada M5S 1A4 (416) 978-4058 clarke@csri.toronto.edu or clarke@csri.utoronto.ca or ...!{uunet, pyramid, watmath, ubc-cs}!utai!utcsri!clarke