python src/main.py -r 100 -js ex.json
tensorboard --logdir logs/2x256-1579515056
- muda numero de pessoas para ver traffic:
- 100 check
- 300 check
- 500 check
- muda os custos
- menos para autocarro check
- mais para carro(portagem) +1 check
- mudar o tempo
- autocarro check
- mudar conforto
- autocarro check
- mais pessoas a partilhar
3000 episodes
-
run 1
- 100 pessoas
- tudo igual
-
run 2
- 300 pessoas
- tudo igual
-
run 3
- 500 pessoas
- tudo igual
-
run 4
- 1 custo autocarro
-
run 5
- custo carro + 2 custo shared + 2/3
-
run 6
- mudar tempo do autocarro + ou - dependendo se pessoas gostam do autocarro
-
run 7
- mudar conforto do autocarro + ou - dependendo se pessoas gostam do autocarro
- Add people that choose a mean of transport
- Write stats to a file
- Think about others possible parsers, maybe for population
- Think about attributes the population will have - relationships
- Utility function - paper
- Reinforcement learning
- Stats about occupancy of edges, type of actors, number people chose each service, utility
- Bus event 10 in 10 minutes?
- Incentives - think about how Cat can introduce them later in an easy breazy way
- Utility factors- how to account for sociability? For now we are going to only have the awareness of the impact of the chosen service
- Actor occupation chart uses only last few runs
- Make different actors - bus,car,shared car
- Make edges only let certain actors traverse them
- Create routes for actors according to the edges specifications
- Parser for graph
- Make different actors - bus,car,shared car
- Make edges only let certain actors traverse them
- Create routes for actors according to the edges specifications
- Added Users
- Utility function
- Reinforcement Learning
- Users can only choose private car if they have a car
- Utility function can't be divided by 0
- Gif showing the occupation of the edges
- Gif showing people learning
- Each service has one color
- In the process of changing actors_flow to be a dictionary for all services (actors)
- Charts now show statistics for different actors - actor chart and edge chart
- Graph is created based on a json file (no longer hardcoded)
- Added Users
- Users choose (randomly) a transportation method
- Users have the "result" of the commute (time, cost, awareness)
- Added Reinforcement learning
- Tensorboard
- Tried different personality types - need to work on that
- Finaly made a commit with all the changes as of yet
- Users have more information from clusters, factors, courses and grades
- Writing user info to a file at the end of the main (need to think about a new place)
- Users now have salary and budget
- Fixed willingness to pay so that it now has to do with the salary of the user