Re: [R] Noisy objective functions

2023-08-13 Thread J C Nash
More to provide another perspective, I'll give the citation of some work with Harry Joe and myself from over 2 decades ago. @Article{, author = {Joe, Harry and Nash, John C.}, title = {Numerical optimization and surface estimation with imprecise function evaluations}, journal =

Re: [R] OFF TOPIC: chatGPT glibly produces a lot of wrong answers?

2023-08-13 Thread Jim Lemon
Hi Bert, The article notes that chatGPT often gets the concept wrong, rather than the facts. I think this can be traced to the one who poses the question. I have often encountered requests for help that did not ask for what was really wanted. I was recently asked if I could graphically concatenate

Re: [R] Noisy objective functions

2023-08-13 Thread Hans W
Thanks, Ben. For certain reasons, I would *not* like to apply global optimization solvers, e.g., for reasons of higher dimensions and longer running times. I was hoping for suggestions from the "Stochastic Programming" side. And please, never suggest `optim` with method "SANN". See the

Re: [R] OFF TOPIC: chatGPT glibly produces a lot of wrong answers?

2023-08-13 Thread CALUM POLWART
It does often behave better if you say to it "that doesn't seem to be working" and perhaps some error message It is afterall a language tool. Its function is to provide text that seems real. If you ask it a science question and ask it to provide references in Vancouver format, it can format the

Re: [R] Noisy objective functions

2023-08-13 Thread Ben Bolker
This is a huge topic. Differential evolution (DEoptim package) would be one good starting point; there is a simulated annealing method built into optim() (method = "SANN") but it usually requires significant tuning. Also genetic algorithms. You could look at the NLopt list of

[R] Noisy objective functions

2023-08-13 Thread Hans W
While working on 'random walk' applications, I got interested in optimizing noisy objective functions. As an (artificial) example, the following is the Rosenbrock function, where Gaussian noise of standard deviation `sd = 0.01` is added to the function value. fn <- function(x)

Re: [R] OFF TOPIC: chatGPT glibly produces a lot of wrong answers?

2023-08-13 Thread Stephen H. Dawson, DSL via R-help
Thanks. https://www.wsj.com/articles/with-ai-hackers-can-simply-talk-computers-into-misbehaving-ad488686?mod=hp_lead_pos10 Ever heard of AI prompt injection? *Stephen Dawson, DSL* /Executive Strategy Consultant/ Business & Technology +1 (865) 804-3454 http://www.shdawson.com On 8/13/23

[R] OFF TOPIC: chatGPT glibly produces a lot of wrong answers?

2023-08-13 Thread Bert Gunter
**OFF TOPIC** but perhaps of interest to some on this list. I apologize in advance to those who may be offended. The byline: "ChatGPT's odds of getting code questions correct are worse than a coin flip But its suggestions are so annoyingly plausible"