| def fact(n : Int):Int = n match | |
| { | |
| case 1 => 1 | |
| case _ => n * fact(n-1) | |
| } |
| def fact_tail(n:Int, holder:Int):Int = n match | |
| { | |
| case 1 => holder | |
| case _ => fact_tail(n-1, n*holder) | |
| } |
| def fib(n : Int):Int = n match | |
| { | |
| case 0 => 0 | |
| case 1 => 1 | |
| case _ => fib(n-1) + fib(n-2) | |
| } |
| def fib_tail(n: Int, a: Int = 1, b: Int = 1):Int = n match | |
| { | |
| case 0 => 0 | |
| case 1 | 2 => b | |
| case _ => fib_tail(n - 1, b, (a + b)) | |
| } |
| // Legacy | |
| abstract class Lannister { | |
| def payTheirDebts: Boolean | |
| def trueLannister = payTheirDebts | |
| } | |
| //Father | |
| trait Tywin extends Lannister{ | |
| override def payTheirDebts = true | |
| } |
| // Legacy | |
| abstract class Lannister { | |
| def payTheirDebts: Boolean | |
| def trueLannister = payTheirDebts | |
| } | |
| //Father | |
| trait Tywin extends Lannister{ | |
| override def payTheirDebts = true | |
| def debt: Int |
| // Legacy | |
| abstract class Lannister { | |
| def payTheirDebts: Boolean | |
| def trueLannister = payTheirDebts | |
| def debt: Int | |
| def addToDebt(amount: Int): Int | |
| } | |
| //Father | |
| trait Tywin extends Lannister{ |
| { | |
| "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json", | |
| "basics": { | |
| "name": "Saheb Motiani", | |
| "label": "loves debugging Distributed Systems; enjoys Functional Programming.", | |
| "image": "", | |
| "phone": "", | |
| "url": "", | |
| "summary": "I care about software performance, robustness, and resiliency. \n\nI crave mysteries, love investigations, and am always hunting for weird issues in systems around me. \n\nMost of my professional experience has been in developing product-based application-level software, but I am also interested in low-level system programming, networks, databases, operating-systems, and developer tools.", | |
| "location": { |
Hey
The journey from the first simple bots to superhuman AI like Libratus and Pluribus is a fascinating 27-year story of academic rivalries, commercial scandals, and massive algorithmic breakthroughs. It's a perfect case study in AI for imperfect information games.
I've written up a little history, from the first academic attempts in 1998 to the modern "GTO Solvers." Grab a coffee, this is a long one.
