Every-visit Monte-Carlo Suppose we Have a continuing task. What/if we cannot set the starting state arbitrarily? i.e. we have a single long trajectory with length NNN s1,a1,r1,s2,a2,r2,s3,a3,r3,…s_1,

TCP reliable data transfer TCP ACK generation Arrival of in-order segment with expected seq #. One other segment has ACK pending | Immediately send single cumulative ACK, ACKing both in-order segme

TCP reliable data transfer TCP ACK generation Arrival of in-order segment with expected seq #. One other segment has ACK pending | Immediately send single cumulative ACK, ACKing both in-order segme

Reliable Data Transfer: Intuition Selective Repeat receiver individually acknowledges all correctly received pkts sender only resends pkts for which ACK not received sender window Selective repeat

Reliable Data Transfer: Intuition rdt reliable data transfer protocol udt unreliable data transfer protocol Reliable Channel channel is perfectly reliable: no bit errors no loss of packets Channe

Model-based RL with a sampling oracle (Certainty Equivalence) Cont’d To find QM^⋆Q^\star_{\hat{M}}QM^⋆​ with empirical R^\hat{R}R^ and P^\hat{P}P^ : f0∈RSA,fk∈T^fk−1.f_0 \in \mathbb{R}^{SA}, \quad f_k

The Learning Setting planning and learning Planning: given MDP model, how to compute optimal policy The MDP model is known Learning: MDP model is unknown collect data from the MDP: (s,a,r,s′)(s,a,r

Consensus Each process proposes a value. All processes must agree on one of the proposed values. Required Properties Termination: Eventually each process sets its decision variable. Liveness Agr